Jobs Data Science

Key responsibilities

• Own end-to-end solution architecture for data, analytics, and AI use cases, with accountability for design quality, security, scalability, supportability, and cost.
• Translate business needs into practical technical designs, target architectures, integration patterns, and delivery-ready implementation guidance.
• Lead by example through hands-on prototyping, architecture reviews, troubleshooting, code/design reviews, and technical support for delivery teams.
• Ensure security, governance, compliance, and operational readiness are built into solutions from design through production deployment.

Must have

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• 10+ years of IT experience, including 5+ years in senior solution architecture roles for enterprise data, analytics, and AI platforms.
• 5+ years strong hands-on experience with Azure-based data platforms, including Azure Data Factory, Databricks, data lake architectures, SQL, and dimensional data modeling, with the ability to build practical end-to-end solution designs.
• Strong experience with enterprise security, governance, and compliance, and the ability to work effectively with enterprise architects and guiding or regulatory functions to ensure solutions meet organizational standards and control requirements.
• Enterprise AI enablement experience: designing solutions with Azure OpenAI and retrieval-augmented (RAG) patterns.
• BI/analytics architecture experience with Power BI or a similar enterprise BI technology.

Advantages

• Deep hands-on expertise in Power BI architecture, including semantic models, DAX, Power Query, workspace strategy, governance, performance optimization, and enterprise reporting patterns.
• Experience with Microsoft-first AI platforms and services such as Azure AI Foundry, Copilot Studio, Azure AI Search, Semantic Kernel, Prompt Flow, and enterprise AI governance patterns.
• Experience with Microsoft Fabric, Azure DevOps, GitHub Enterprise, and CI/CD for Data or AI solutions.
• Experience with Microsoft security and governance services such as Microsoft Entra, Purview, and Key Vault.
• Experience in life sciences, pharmaceuticals, or other regulated industries.
• Relevant Microsoft certifications in Azure, Power BI, data, or AI architecture.

Key skills

• Hands-on technical leadership with a clear lead-by-example mindset.
• Strong architecture judgment across data, analytics, AI, integration, security, and non-functional requirements.
• Proven ability to own solution architecture end to end: shape target designs, validate them through prototyping or proof of concept where needed, guide delivery teams through implementation, and provide technical oversight through design reviews and production readiness checks.
• Ability to translate business problems into practical, delivery-ready technical solutions.
• Strong troubleshooting, decision-making, estimation, and risk management capability.
• Comfort working across distributed teams and external suppliers in enterprise delivery environments.
• Excellent communication skills in English, with the ability to drive alignment across architects, delivery teams, business stakeholders, and enterprise control functions.

Core technology stack

• Analytics: Power BI, semantic models, DAX, Power Query, Databricks, enterprise reporting and governance.
• Data platform: Azure Data Factory, Databricks, Azure data lake, SQL, dimensional modeling, ETL/ELT, orchestration.
• AI platform: Azure OpenAI, Azure AI Foundry, Azure AI Search, Copilot Studio, Semantic Kernel, Prompt Flow.
• Engineering and governance: Azure DevOps, GitHub Enterprise, CI/CD, Microsoft Entra, Purview, Key Vault.
• Optional / advantageous: Microsoft Fabric, Python, data observability and monitoring patterns.

In Competera, we are building a place where optimal pricing decisions can be made easily. We believe that AI technologies will soon drive all challenging decisions and are capable of helping humans be better. We are now looking for a Strong Middle Data Scientist to play a key role in reshaping the way we provide our solutions.

You could be a perfect match for the position if
You want to:

• Analyze retail data to find patterns and derive insights for data-aware pricing strategies.
• Maintain, tune and improve existing models, investigate model performance issues and identify their root causes.
• Design and validate (proof-of-concept) POC for new modeling approaches, challenging existing assumptions when needed.
• Own complex SnD Data science solution implementation for new clients end-to-end: validate business requirements and data, map requirements to existing tools and functionalities, develop and evaluate models and bring the solution into production.
• Research, prototype and evaluate modelling approaches for new domains and challenging cases such as sparse demand, promotions and changing sales patterns.
• Collaborate with Data Scientists, Engineers, Product/Project Managers and domain experts to improve and bring to production new approaches of demand modeling.

You have:

• 3+ years of commercial experience in Data Science/Machine Learning or related field.
• Solid mathematical background preferably in Computer Science, Mathematics, Statistics or another quantitative field.
• Strong knowledge of statistics, classical machine learning, deep learning methods and commonly used forecasting approaches.
• Practical experience with time series forecasting methodologies.
• Proficiency in scientific Python toolkit including NumPy, pandas, scikit-learn, gradient-boosting frameworks such as CatBoost/LightGBM and either Keras/TensorFlow or PyTorch.
• Experience with statistical hypothesis testing and experimental design, including A/B testing.
• Advanced SQL skills for data manipulation and extraction.
• Strong Python skills and experience writing clean, modular, maintainable code for prototyping and performing experiments.
• English sufficient for technical discussions, documentation, and collaboration in international environment (Upper-intermediate and higher level).

Desirable requirements:

• Experience in retail, e-commerce, pricing, revenue management or marketplaces.
• Experience working with large datasets and distributed processing tools such as. Pyspark/Spark/Databricks.

​Soft skills:

• Analytical mindset and critical thinking to solve complex problems.
• Strong ownership: you take responsibility for problems end-to-end, proactively drive them forward and stay accountable for the quality and impact of the final solution
• Agile approach, with the ability to experiment and test hypotheses in a dynamic business environment.
• Business-oriented thinking, capable of translating complex models into clear business insights.
• Curiosity and a drive for continuous learning in the data domain.
• Strong team player, able to collaborate across cross-functional teams.

You’re gonna love it, and here’s why:

• Rich innovative software stack, freedom to choose the best suitable technologies.
• Remote-first ideology: freedom to operate from the home office or any suitable coworking.
• Flexible working hours (we start from 8 to 11 am) and no time tracking systems on.
• Regular performance and compensation reviews.
• Recurrent 1-1s and measurable OKRs.
• In-depth onboarding with a clear success track.
• Competera covers 70% of your training/course fee.
• 20 vacation days, 15 days off, and up to one week of paid Christmas holidays.
• 20 business days of sick leave.
• We reimburse the cost of coworking.

Drive innovations with us. Be a Competerian.

Automat-it is an all-in AWS Premier Partner and Managed Services Provider specializing in the startup ecosystem. With over 800 customers and 500+ AWS certifications, Automat-it brings hands-on expertise in AI, DevOps, and FinOps to empower fast-paced startups to grow, deliver & win. Our customers save significant time-to-market and optimize their cloud performance and costs.

We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.

We’re looking for a Senior Data Scientist to join our Data Science practice and work directly with customers on complex AI and Machine Learning projects on AWS.

This is not a traditional analytics or research-focused Data Science role. You’ll work across classical ML, fine-tuning, GenAI, multimodal systems, and production ML on AWS, helping customers decide which technical approach actually fits their problem.

You’ll own projects end-to-end: understand the customer’s domain and data, evaluate different solution paths, define the architecture, implement the critical parts, and guide delivery through production.

📍 Work location: remote from Ukraine

If you are interested in this opportunity, please submit your CV in English.

Key Responsibilities

• Own Data Science projects end-to-end: Take customer problems from technical discovery through data analysis, solution design, experimentation, implementation, deployment, and production validation.
• Choose the right technical approach: Evaluate whether a problem should be solved with prompt engineering, RAG, GenAI, agentic workflows, fine-tuning, smaller language models, classical ML, Computer Vision, recommendation systems, or custom model training.
• Work deeply with data: Analyze and prepare customer datasets, identify data quality issues, create representative validation and golden datasets, and ensure the available data can support the chosen modelling approach.
• Build and fine-tune ML models: Train, fine-tune, optimize, evaluate, and deploy models using Python, PyTorch/TensorFlow, SageMaker, and modern ML tooling.
• Work with Generative AI: Build and evaluate GenAI solutions using Amazon Bedrock, RAG, prompt engineering, model selection, agentic workflows, and related AWS-native AI services.
• Use SageMaker in production: Work with SageMaker Studio, training jobs, endpoints, pipelines, model registry, batch inference, monitoring, and other production ML capabilities.
• Design production-ready solutions: Make architecture decisions across quality, latency, cost, scalability, maintainability, observability, and operational complexity.
• Work directly with customers: Participate in technical discovery, workshops, architecture discussions, and delivery conversations with founders, CTOs, engineering teams, and technical stakeholders.
• Challenge technical assumptions: Help customers avoid unnecessary complexity, explain trade-offs, costs and recommend simpler or more effective approaches when appropriate.
• Lead through technical ownership: Independently own projects with minimal supervision and mentor less experienced Data Scientists and engineers when needed.

• Collaborate across teams: Work closely with AI Engineers, MLOps, Data Engineering, DevOps, and Solution Architecture teams on customer solutions that cross multiple technical domains.

   

Requirements

• 5+ years of experience in Data Science, Machine Learning, Applied Science, or a closely related role.
• Strong classical Machine Learning fundamentals and hands-on experience building production ML solutions.
• Deep practical experience working with data, including data preparation, validation, feature engineering, dataset construction, and model evaluation.
• Strong Python skills and hands-on experience with PyTorch and/or TensorFlow.
• Strong practical experience with AWS SageMaker beyond notebook-level usage, including model training, deployment, inference, pipelines, or production operations.
• Hands-on experience with Amazon Bedrock and modern Generative AI approaches.
• Practical experience with fine-tuning models and understanding when fine-tuning is preferable to prompting, RAG, or other approaches.
• Experience in at least one strong ML domain such as NLP, Computer Vision, recommendation systems, forecasting, structured ML, multimodal ML, or similar.
• Understanding of RAG, embeddings, prompt engineering, foundation models, and agentic workflows.
• Strong understanding of MLOps and production ML practices, including model deployment, monitoring, reproducibility, lifecycle management, and CI/CD.
• Experience designing and owning solutions independently rather than working only from predefined technical specifications.
• Strong customer-facing communication skills and ability to explain technical trade-offs clearly.
• Ability to work with ambiguity, messy real-world data, and changing customer requirements.

• Strong technical judgment and a pragmatic approach to balancing model quality with delivery speed, cost, and business value.

   

Nice to have

• Experience with AgentCore, Bedrock Agents, LangGraph, Strands Agents, or other agentic frameworks.
• Experience with Small Language Models or domain-specific model adaptation.
• Experience with recommendation systems, audio ML, signal processing, or multimodal systems.
• Experience in technical consulting, pre-sales, or customer discovery.
• AWS Machine Learning certifications.
• Master’s degree or PhD in Computer Science, Machine Learning, Data Science, Mathematics, Statistics, or a related field.

What Success Looks Like in Year One

• Independently owns assigned data projects end-to-end, from understanding the problem and making technical decisions to implementation, troubleshooting, testing and successful delivery, with minimal supervision.
• Has built strong practical expertise across the team’s core data stack and can confidently work across different customer environments, including Spark, Python/SQL, data lakes/lakehouses, analytical and NoSQL databases, streaming and other technologies used by the team.
• Can investigate unfamiliar data problems independently, identify performance or data-modeling issues, understand upstream/downstream dependencies, and recommend pragmatic solutions to customers.
• Continuously expands technical depth, keeps up with modern Data technologies and patterns, and can quickly learn new technologies as customer projects and the Data practice evolve.
   

Automat-it is committed to fostering a workplace that promotes equal opportunities for all. We firmly believe that cultivating a diverse workforce is crucial to our success. Our recruitment decisions are grounded in your experience and skills, recognizing the value you bring to our team.

Type: Full-time, remote
Location: EU + CIS + Balkans (citizenship doesn't matter — what matters is current location and the jurisdiction from which access to client servers would occur)
Contract: 12 months, long-term, with potential for extension
Start date: Early September 2026 (ASAP)
Time zone: CET
English: B2 minimum, C1 preferred

About the Role

We're looking for a senior Data Architect to design and modernize an Azure data platform, including the data architecture underpinning GenAI/RAG/Agentic applications. This is an architecture role, not hands-on RAG/ML development — the focus is on how enterprise data and knowledge are ingested, prepared, stored, governed, and made available for retrieval and AI consumption.

Must-Haves

• Azure Cosmos DB — hands-on experience with data modeling, partitioning, indexing, RU/throughput and cost optimization, consistency, Change Feed
• Proven experience designing data platforms supporting GenAI/RAG use cases
• AI-ready data architecture experience
• A real project where the candidate designed or contributed to the data architecture supporting a RAG, GenAI, or Agentic AI application
• Azure Synapse Analytics — depth across workload patterns (Pipelines, Spark, Serverless SQL, Dedicated SQL Pools)
• Azure Databricks
• Azure SQL MI / SQL Server / T-SQL
• Azure Data Lake / Lakehouse architecture
• Azure Functions
• Experience with structured and genuinely unstructured data (documents, PDFs, scans, images, email, free text)
• Metadata/configuration-driven ingestion — reusable, scalable design for onboarding new data sources
• Demonstrated architecture ownership — real decisions made, not just pipeline implementation
• At least 4 years of recent (not dated) hands-on Azure experience
• Must be an Architect by role, not a Data Engineer

What You'll Do

• Take over an existing, problematic data platform, quickly assess it, and deliver both tactical fixes and a longer-term target architecture
• Design a reusable ingestion architecture for heterogeneous sources (databases, APIs, files)
• Make technology-neutral calls on when Databricks/Synapse/ADF are actually needed — and when they're not
• Produce detailed, implementation-ready architecture documentation for engineering teams
• Own data governance, data quality, and incremental processing
• Communicate effectively with both technical and business stakeholders

A Note on GenAI/RAG

You won't be building RAG solutions or AI agents yourself. What's required is experience designing the data architecture around such applications — how enterprise data and knowledge get ingested, processed, indexed, and made available for retrieval and AI consumption (document processing, OCR, chunking, embeddings, vector search, etc.), including where Cosmos DB fits into that picture.

Interview Process

1. Intro call
2. Technical interview (~1 hour)

Be ready to walk through 2–3 concrete project examples using: problem → options considered → your decision → rationale → implementation → result. The focus is less on definitions and more on how you think as an architect and how quickly you can turn a messy existing situation into practical direction for an engineering team.

We are seeking an experienced Senior Data Technology Consultant to join our growing Data & AI practice. This role bridges technology with business value, helping clients harness the power of data to drive transformative business results. You will play a pivotal role in crafting innovative data solutions, supporting sales efforts, and delivering exceptional value to our clients through strategic consulting and technical expertise.

This is an exciting opportunity to work with cutting-edge technologies and make a tangible impact across global industries.

Kindly note that this role supports remote work, but only from within Ukraine.

Responsibilities

• Work closely with sales, delivery, and expert teams to align client needs with data-driven solutions, effectively connecting business challenges to our offerings
• Own the end-to-end presales process, including opportunity qualification, solution design, proposal development, demos, and client presentations
• Lead workshops and meetings with clients to gather business objectives and technical requirements, ensuring alignment between client goals and our solutions
• Architect tailored data solutions, encompassing cloud-native platforms, data integration, advanced analytics, and AI/ML models, to provide actionable business insights
• Develop competitive proposals, pricing models, and value propositions to successfully close opportunities and secure engagements
• Stay updated on emerging trends in Data & Analytics, Cloud, and AI, providing strategic advice to clients and supporting innovation within the practice
• Contribute to the development of reusable solution frameworks, accelerators, and methodologies to drive operational efficiency
• Act as a mentor and knowledge-sharer across the team, supporting skill-building and best practice dissemination

Requirements

• Extensive experience in presales, solution architecture, or consulting, with a focus on Data/AI technologies and related business use cases
• Strong technical knowledge in legacy Data Warehouse platforms (Oracle, DB2, Informatica, SSIS, etc.)
• Good experience in cloud data technologies (AWS, Azure, GCP)
• Experience in modern data platforms (Databricks, Snowflake)
• Familiarity with data science techniques and proficiency in analysis of client needs to align with technical solutions
• Excellent communication and storytelling skills—able to translate complex technical concepts into clear, client-friendly narratives
• Proven track record in engagement with senior stakeholders and delivery of impactful presentations or pitches
• Experience in creation of detailed proposals, RFP responses, and pricing/engagement models for data-related services or projects
• Understanding of strategic consulting principles and the ability to develop future-state recommendations and roadmaps for client success
• Strong organizational, leadership, and project scoping abilities, with a proven ability to manage complex tasks in a fast-paced environment
• Bachelor’s or master’s degree in data science, Computer Science, Business Analytics, or a related field (or equivalent professional experience)
• Excellent English communication skills, with the ability to clearly and effectively explain technical concepts to diverse audiences

We offer/Benefits

With us you can:

• Work on a flexible schedule remotely or from any of our comfortable offices or coworking spaces in Ukraine
• Receive the necessary equipment to perform your work tasks
• Change projects and technology stacks within EPAM
• Gain experience in various business domains (Insurance, E-commerce, Healthcare, Finance, Travelling, Media, Artificial Intelligence, and more)
• Relocation opportunities may be available for eligible candidates, depending on the role and openings at other EPAM locations
• Participate in volunteer, charity programs and communities (both technical and interest-based)

We focus on your professional growth:

• You can plan your individual career path together with your manager
• Receive regular feedback from colleagues
• Improve your English for free with certified teachers (Speaking Clubs, client interview preparation courses, etc.)
• Get the opportunity to undergo free training and certification in AWS, GCP, or Azure Clouds
• Use the internal E-learn training program (18,200+ specialized training and mentoring programs)
• Access corporate accounts on LinkedIn Learning, Get Abstract and other partner resources
• Study at EPAM Solution Architecture School with the instructors who are practicing architects
• Develop as a leader, join Delivery Management, Resource Management, Leadership Essentials school and more
• Participate in internal communities (500+ meetups, technical discussions, brainstorming sessions, online events and conferences annually)

What we offer:

• Vacation and sick leave (including a sick leave without a medical certificate)
• A wide range of Voluntary Medical Insurance programs providing both medical treatment and various preventive options (including sports activities)
• Medical insurance for family members at corporate rates
• Company support during significant life events (childbirth or adoption, marriage, etc.)
• Support for psychological comfort: discounts on services from mental health specialists or coaches, thematic training
• E-kids program — a free programming language training program for EPAMers’ children

Kindly be advised that the set of benefits, including learning, certification, and other opportunities, may vary depending on the role you apply for. Our recruiter will be able to share more details about the specific opportunity during your general interview.

We are looking for a Computer Vision Engineer to design and implement visual intelligence systems that power personalized digital experiences across connected devices and mobile applications.

This is a hands-on role focused on applied computer vision - from model design and training to on-device deployment. You will work at the intersection of deep learning, image and video processing, and product integration, collaborating closely with backend engineers, ML engineers, and product managers to bring vision-driven features into production and continuously optimize them for real-world usage and resource-constrained environments.

Responsibilities:

• Design, train, and deploy computer vision models for use cases such as object detection, classification, segmentation, and visual analysis;
• Build and maintain data pipelines for image and video processing, including annotation, augmentation, and dataset versioning workflows;
• Optimize models for inference on edge and mobile devices (quantization, pruning, distillation, hardware-accelerated runtimes);
• Collaborate with product and engineering teams to translate product ideas into vision-powered features;
• Implement model observability, monitoring, and retraining workflows for models running in production;
• Contribute to the architecture of a modern ML platform within a cloud-native microservices environment;
• Work with backend and mobile teams to expose model outputs via APIs and integrate them into customer-facing experiences;
• Evaluate emerging CV/AI research and assess promising methods for future implementation.

Requirements:

• 3+ years of experience in applied computer vision or machine learning with a strong CV focus;
• Strong knowledge of:
  • Deep learning for vision: CNNs, object detection and segmentation architectures (e.g. YOLO, Faster R-CNN, U-Net), and modern vision transformers;
  • Python and ML libraries such as PyTorch, TensorFlow, OpenCV;
  • Building, deploying, and maintaining CV models in production.
• Familiarity with:
  • Model optimization and on-device inference (ONNX, TensorRT, TensorFlow Lite, Core ML, OpenVINO);
  • MLOps tools (e.g. MLflow, TFX, Airflow, Vertex AI);
  • Data and video pipelines (e.g. Kafka, BigQuery, FFmpeg, GStreamer);
  • Model serving frameworks (e.g. FastAPI, TensorFlow Serving, TorchServe).
• Experience with cloud platforms (GCP, AWS, or Azure) and container-based deployments;
• Comfortable collaborating with product, engineering, and analytics teams;
• Bonus: Experience with edge AI, mobile ML, multi-modal models, or real-time video processing at scale.

We Offer:

• Remote work and flexible working hours.
• Legal support.
• Paid sick leaves.
• Paid vacations.
• Medical insurance. 
• Free English classes.

We are looking for a Computer Vision Engineer with strong experience in deep learning and applied computer vision systems.
The role involves working on challenging CV problems in real-world environments.
We consider Middle and Senior engineers, with scope adapted to experience.
Responsibilities

• Develop, train, and optimize deep learning models for:
  • image retrieval
  • image matching (keypoint detection and matching)
  • auxiliary perception tasks supporting the main pipeline
• Evaluate models using quantitative metrics, including:
  • retrieval quality (mAP, Recall@K)
  • matching performance (precision/recall, repeatability)
  • end-to-end system metrics (accuracy, latency, robustness)
• Optimize models for production deployment using modern toolchains:
  • ONNX / TensorRT / OpenVINO / edge acceleration where applicable
  • model compression techniques (quantization, pruning, distillation)
  • latency, memory, and throughput optimization
• Work with large-scale visual datasets and descriptor-based representations
• Collaborate with engineering teams to integrate models into production systems

Required Qualifications

• 2–4+ years of experience in Computer Vision / Deep Learning
• Hands-on experience with keypoint detection and matching models (e.g. SuperPoint, R2D2, DISK, LightGlue, SuperGlue)
• Experience with image retrieval or metric learning systems
• Strong understanding of geometric and motion-related computer vision concepts:
  • keypoint detection and description
  • image matching and geometric verification (RANSAC, homography, PnP)
  • pose estimation and refinement techniques (PnP, bundle adjustment, pose graph optimization)
  • optical flow and frame-to-frame tracking
  • vector search / ANN methods for descriptor retrieval
• Strong Python skills (PyTorch and scientific computing stack)
• Ability to read and understand inference code in C++

Nice to Have

• Experience with noisy or imperfect real-world datasets
• Self-supervised or unsupervised learning methods (contrastive learning, homography supervision, etc.)
• Experience optimizing models for edge deployment (quantization, pruning, distillation)
• Familiarity with FAISS or similar vector search systems
• Experience with optimization libraries for geometric problems (bundle adjustment, pose refinement)
• Understanding of real-time constraints (latency, memory, CPU inference budgets on ARM or low-power x86 systems)

ZentixSoft is looking for a Senior Data Solutions Consultant / Solution Architect! 🚀

Format: Project-Based / Hourly Engagement (Remote). 

💡 Why ZentixSoft?

💸 Fair Compensation: Transparent hourly/project-based rates for expert consulting hours.

⚖️ Work-Life Balance: Flexible scheduling tailored around your primary availability.

🦾 Trust & Freedom: Pure professional autonomy with zero micromanagement and no time-trackers.

🎁 Culture & Community: A collaborative environment where your architectural decisions directly drive business outcomes.

🧩 Project & Role Overview:

You will support our technical and presales teams during the discovery and solution design phase of a complex product data management initiative (handling legacy data sources, supplier onboarding, taxonomy, attribute mapping, and multi-system synchronization).

 Discovery & Workshops: Participate in client-facing discovery sessions and technical workshops to unpack legacy architecture and business constraints.

 Architecture Design: Analyze product-data flows, identify systems of record, and distinguish between integration/ETL challenges versus semantic data-mapping issues.

 Roadmap & Strategy: Define realistic target architecture options, phased implementation roadmaps, and potential pilot use cases.

 PIM / MDM & AI Integration: Evaluate approaches for supplier data onboarding, taxonomy harmonization, and assess where AI/LLM automation adds real value vs. deterministic rules/governance.

 Proposal Support: Help formulate solution proposals, architecture diagrams, and technical recommendations for business and technical stakeholders.

🎓 Our Perfect Match (Requirements):

 Domain Experience: 5+ years of hands-on experience in data architecture, system integrations, and solution design.

 PIM / MDM / Product Data Expertise: Strong background in Product Information Management (PIM), Master Data Management (MDM), product taxonomy, attribute mapping, and supplier onboarding.

 Platform Exposure: Experience with platforms such as Akeneo, Salsify, Stibo Systems, Informatica, Contentserv, Pimcore, or inriver (or similar product catalog ecosystems).

 Technical Integration & Data Quality: Familiarity with ERP/PIM/e-commerce integrations, product data standards (e.g., BMEcat), data deduplication, golden-record concepts, and legacy SQL/Access environments.

 Modern Tech Evaluation: Understanding of AI/LLM-assisted data classification and automated mapping techniques.

 Consulting & Communication: Proven experience leading technical workshops with clients, with Fluent / Confident English for client-facing communication.

📍 Engagement Details:

⏳ Format: Project-based / Hourly consulting that can be easily combined with your full time occupation.

📍 Location: 100% Remote.

We look forward to reviewing your profile:

We are looking for a Senior Data Scientist / Python Developer to join an R&D-oriented team working on intelligent solutions for telecommunications and network monitoring.

This is a hybrid role combining strong Python development, Data Science, Machine Learning/AI, statistics, and algorithm design. You will work on solutions for real-time detection and analysis of network and service issues.

What you’ll do:

Develop production-ready solutions using Python

Design and implement ML/AI algorithms for real-time detection of network and service issues

Apply statistics, data analysis, and algorithmic approaches to complex technical problems

Work with Machine Learning and AI technologies, including LLMs

Develop and optimize data-driven detection and monitoring solutions

Contribute to the design of algorithms and data processing approaches

Work closely with an experienced R&D-oriented engineering team

Follow software engineering best practices, including CI/CD, testing, and version control

Work in a Linux environment and contribute to agile development processes

Requirements:

3–5+ years of professional software development experience

Strong Python development skills

Solid background in Data Science / Machine Learning / AI

Experience with statistics and algorithm design

Practical experience with ML/AI, including LLMs

Experience with real-time data processing, detection, monitoring, or anomaly detection is highly relevant

Experience with CI/CD

Good knowledge of Linux

Strong analytical and problem-solving skills

Fluent English — you will work in an international R&D environment

Education

A Master’s degree in one of the following fields is expected:

Computer Science

Physics

Mathematics

Communications Engineering

A PhD is a strong plus, especially for candidates with an R&D or research-oriented background.

Nice to have:

Experience in telecommunications

Knowledge of telecommunications networks

Experience with network monitoring, anomaly detection, or service reliability

Research or R&D experience

Experience working with highly technical engineering teams

What We Offer:

-Paid vacation and sick leave

-We provide the equipment you need to work comfortably (if required)

-We cover 50% of courses if you want to grow professionally

-Regular salary reviews based on your performance

-Competitive salary, depending on your experience

-Always on-time payments — no delays

-A normal, supportive team without unnecessary bureaucracy

About Playtech                               

Founded in 1999, the company has a premium listing on the Main Market of the London Stock Exchange and is focused on regulated and regulating markets across its B2B and B2C businesses. Both divisions leverage Playtech’s proprietary technology to deliver innovative products and services to ensure a safe, engaging and entertaining gaming experience. 

Playtech is the gaming industry's leading technology company delivering business intelligence-driven gaming software, services, content, and platform technology across the industry. 

Read more about who we are and what we do here: www.playtechpeople.com  

Here at Playtech, we genuinely believe that people are our biggest asset. Diverse thoughts, experiences, and individual characteristics enrich our work environment and lead to better business decisions. Recognizing differences and ensuring our processes are transparent is the core of Playtech's overall commitment to responsible business practices. 
 

Ready to level up your career?

Our innovative BI unit is looking for a passionate Data Scientist to join the team. If you thrive on working with cutting-edge technologies and are eager to enhance our systems, we want to hear from you. Join us to drive impactful projects in a dynamic and forward-thinking environment.

Job Description

Your influential mission. You will...

• Develop production data science applications in Python, end to end.
• Design and develop new AI services from scratch.
• Maintain and enhance current data science pipelines in complex high-load applications.
• Collaborate closely with R&D and DevOps teams.
• Research, invent and adapt machine learning algorithms for dedicated business needs.
• Perform predictive and statistical modelling.
• Perform ad-hoc analyses as required.

Qualifications

Components for success. You...

• Bring a minimum of 4 years of experience as a Python developer (including familiarity with PyCharm, git, and debugging).
• Possess a minimum of 3 years of experience in predictive modeling, preferably within data science production services..
• Have at least 3 years of experience in tabular or time series data analysis in a data developer, or data scientist role.
• Write clean, maintainable, production-ready code, following best practices for testing, reliability, scalability, and code quality.
• Demonstrate proficiency in SQL for data manipulation and visualization.
• Are a strong team player, with excellent communication skills, capable of working collaboratively in a remote environment.
• Have a high level of English proficiency.
• Hold a Bachelor's degree in Engineering, Economics, Mathematics, Statistics, or similar.
   

You'll get extra points for...

• Knowledge of AWS or GCP.
• Master's degree in Engineering, Economics, Mathematics, Statistics, or similar.
• Having experience in direct communication with business.
   

Thrive in a culture that values...

• Engaged User Experiences - We develop personalized recommendations and churn mitigation strategies to keep users coming back for more.
• Data-Driven Decision Making -  We generate insightful reports to empower informed decisions across the organization.
• Cutting-Edge Technologies -  We're constantly exploring and integrating new technologies to enhance our capabilities.
• Responsible Development - We prioritize responsible user experiences through innovative solutions.

Additional information

BI Unit
We're a dynamic and innovative team of 30 developers, with expertise in data science, Python development, data engineering, front-end development, and DevOps. We're passionate about pushing boundaries and developing solutions that make a positive impact.

Join us and be a part of the future!
 

Playtech is an equal opportunities employer. Our mission is to welcome everyone and create inclusive teams. We celebrate differences and encourage everyone to join us and be themselves at work.

We are looking for an experienced and product-minded Lead Data Scientist to drive the evolution of our Data Science function, shape the technical vision, and guide a high-impact team working at the intersection of research and production. This is a unique opportunity to influence strategy, lead cross-functional teams, and build ML solutions that directly power mission-critical business decisions

What You Will Do

• Define and own the Data Science strategy, ensuring alignment with business goals and long-term product vision.
• Shape and maintain the technical roadmap based on business priorities, team capacity, and company growth.
• Scale the Data Science function as the organization expands, designing team structure and hiring profiles.
• Lead, hire, and mentor a cross-functional team of Data Scientists while fostering a strong R&D culture built on rigor and measurable impact.
• Manage resources across both Delivery (S&D) and Research (R&D) squads, ensuring clarity and productivity.
• Act as the bridge between R&D and Delivery: translate business needs into research tasks and adapt prototypes into production-ready solutions.
• Architect client solutions by selecting appropriate models, algorithms, and assortment strategies using our ML stack.
• Serve as the quality gatekeeper: review code, validate A/B test designs, and ensure all work meets the team’s Definition of Done (DoD).
• Drive key DS metrics such as research-to-production time, experiment velocity, and recommendation quality.
• Communicate insights clearly to product managers, engineers, clients, and stakeholders, aligning expectations and next steps.
• Represent the company’s technological excellence to investors and partners during high-stakes due diligence.
• Collaborate with clients' Data Science and Analytics teams (including PhDs), explaining methodology, assumptions, and results with confidence.
• Translate complex model outputs into concise, business-oriented presentations for executives and decision-makers.
• Support the sales and pre-sales process by building compelling technical narratives and showcasing ML capabilities.

• Stay hands-on when needed — from debugging critical delivery issues to prototyping new models or designing experiments.

   

What You Have

• 5+ years of experience in Data Science or a related field, with a strong record of delivering production value.
• Strong Python and SQL proficiency, with clean and modular coding practices.
• Hands-on experience with Databricks and Apache Spark.
• Familiarity with Data Mesh principles and collaboration workflows with data engineering teams.
• Solid mathematical foundation, ideally within a Computer Science–related discipline.
• Expertise in scientific Python tools: NumPy, pandas, scikit-learn, and either TensorFlow/Keras or PyTorch.
• Deep understanding of statistical methods and A/B testing frameworks.
• Experience with Time Series Forecasting approaches.
• 3+ years working with tabular and mixed (multimodal) data.
• Bonus: experience in Causal Inference and ecommerce/retail domains.

• Upper-intermediate or higher English proficiency and excellent public speaking skills.

   

Soft Skills

• A strong focus on business impact — understanding not only how the model works but why it matters.
• Ability to translate complex concepts into simple explanations for non-technical stakeholders.
• Professional communication with highly technical client teams, including PhD-level experts.
• Ownership of data requirements, integration workflows, and validation processes.
• Comfort with experimentation, iteration, and decision-making in a dynamic environment.
• Proactivity: contribute DS-driven ideas to the Product Backlog and influence roadmap direction.
• Creative thinking and a pragmatic approach to solving complex technical and product challenges.

• Curiosity, eagerness to learn, and a strong entrepreneurial mindset.

   

You Will Love Working With Us Because

• Innovative ML stack with freedom to choose the best tools and approaches.
• Remote-first culture with the flexibility to work from anywhere.
• Flexible working hours (start between 8–11 AM), no time tracking.
• Regular performance reviews and clear OKR structure.
• In-depth onboarding with transparent success milestones.
• We cover 70% of your training or course fees.
• 20 vacation days, 15 days off, and an additional week of paid Christmas holidays.
• 20 business days of paid sick leave.
• Partial medical insurance coverage.

In Competera, we are building a place where optimal pricing decisions can be made easily. We believe that AI technologies will soon drive all challenging decisions and are capable of helping humans be better.

We are now looking for a hands-on Leader who can bridge the gap between advanced research and real-world product delivery. You will be the technical anchor for two streams: S&D (Service & Delivery), ensuring our clients get robust, profitable pricing recommendations, and R&D (Research & Development), guiding the strategy for next-gen algorithms.

What you will do

• Have clear vision and own the strategy of Data Science in the organization.
• Shape the technical roadmap based on business needs, team capacity, and long-term strategy.
• Gradually scale data science function with company growth. 
• Define the hiring profile, lead and mentor a cross-functional team of Data Scientists, and cultivate a high-performing R&D culture focused on scientific rigor and measurable business impact.
• Manage resources across both Delivery (S&D) and Research (R&D) squads.
• Act as the main bridge between R&D and S&D: translate business requirements into research tasks, and help the team adapt complex prototypes into stable, production-ready solutions.
• Architect client solutions by selecting the right models and assortment strategies to solve specific business problems using our existing stack.
• Serve as the quality gatekeeper for the team, conducting code reviews, verifying A/B test designs, and ensuring the team hits their Definition of Done (DoD).
• Drive key DS metrics such as research-to-production time, experiment velocity, and the overall quality of price recommendations.
• Communicate clearly with product managers, engineers, and occasionally clients to explain DS trade-offs, present results, and align on next steps.
• Confidently represent the company's technological expertise to investors and partners. You will clearly articulate the Data Science strategy, the core algorithms' defensibility, and the technical roadmap during high-stakes due diligence processes.
• Engage directly with customers' Data Science and Analytics teams (including PhD-level experts). You must be able to confidently explain our methodology, model assumptions, performance results, and address their most technical questions, serving as a critical differentiator during sales and pilot phases.
• Present complex model results, performance metrics, and strategic trade-offs to key stakeholders in a clear, concise, and business-focused manner.
• Support the sales and pre-sales process by building compelling technical narratives that demonstrate our value proposition and deep expertise in the pricing domain.
• Stay hands-on: dive into code and architecture when needed - whether it's designing a new experiment, fixing a critical issue in the delivery pipeline, or prototyping a new idea.

What you have

• 5+ years of experience in Data Science or a related field with a focus on delivering value to production.
• Strong Python and SQL skills, capable of writing modular and readable code for experiments and prototypes.
• Familiarity Databricks data platform and Apache Spark.
• General familiarity with Data Mesh approach and ability to leverage its best practices in collaboration with data engineers.
• Solid mathematical background, preferably in a Computer Science-related field.
• Proficiency in the scientific Python toolkit, including NumPy, pandas, scikit-learn, and either Keras/TensorFlow or PyTorch.
• Deep understanding of statistical testing methodologies, specifically A/B testing design.
• Familiarity with Time Series Forecasting approaches.
• At least 3 years of experience working with tabular and mixed (multimodal) data.
• Expertise in Causal Inference and background in Ecommerce/Retail are strong pluses.
• Upper-intermediate or higher level of English and strong public speaking skills.

Soft skills 

• You care not only about how the model works mathematically but what value it brings to the user and the business.
• Able to translate complex technical concepts into simple business language for stakeholders.
• Able to professionally and clearly communicate with PhD scientists on customer side during the sales process, pilot and rollout.
• Able to own data requirements and build efficient processes to support integration and data engineering with outlining data integration and validation requirements.
• Ready to experiment, pivot, and make data-driven decisions in a dynamic business environment.
• Proactively contribute ideas to the Product Backlog with ideas based on technical knowledge and capabilities.
• Be able to think outside of the box and find simple and elegant solutions to complex problems, including technical, product and processes-related ones.
• Curiosity and a drive to continuously learn within the domain.
• Have a truly entrepreneurial mindset.

You’re gonna love it, and here’s why:

• Rich innovative software stack, freedom to choose the best suitable technologies.
• Remote-first ideology: freedom to operate from the home office or any suitable coworking.
• Flexible working hours (we start from 8 to 11 am) and no time tracking systems on.
• Regular performance and compensation reviews.
• Recurrent 1-1s and measurable OKRs.
• In-depth onboarding with a clear success track.
• Competera covers 70% of your training/course fee.
• 20 vacation days, 15 days off, and up to one week of paid Christmas holidays.
• 20 business days of sick leave.
• We reimburse the cost of coworking.

Drive innovations with us. Be a Competerian.

We are looking for a Principal Backend & Data Architect to own the architecture of a complex data-intensive product from the ground up.

This is a hands-on technical leadership role for someone who has designed production-grade platforms where data modelling, versioning, traceability, permissions and long-term architectural decisions are critical.

What you will own

• Core backend and data architecture
• Domain and data modelling
• Versioned and temporal data structures
• Data provenance, lineage and historical recomputation
• Multi-tenant architecture and data isolation
• Permission models including RBAC / ABAC
• Auditability and traceability
• Computation and semantic layers
• Technical standards and architecture documentation
• Technical leadership and review of backend implementation

What we are looking for

• 8+ years of backend/software engineering experience
• Proven experience architecting complex, data-heavy production systems
• Excellent system design and data modelling skills
• Strong PostgreSQL / SQL expertise
• Experience with distributed systems, queues, background processing and APIs
• Experience with temporal, versioned or event-driven architectures
• Strong understanding of multi-tenancy, authorization and data security
• Ability to make architecture decisions and remain hands-on during implementation
• Experience leading senior engineers technically

Strong advantage

Experience with regulated or sensitive data, healthcare, fintech, insurance, IoT, analytics or decision-support platforms.

This is not a pure management or solution-architecture role. We are looking for someone who can design the foundation, challenge assumptions and stay close to implementation.

We are looking for a highly skilled Senior Data Scientist to join our team.  As a Senior Data Scientist, you will be responsible for designing and implementing advanced data models, analyzing complex business problems, and developing solutions that help optimize sales, marketing, pricing, and overall commercial performance in a leading American publishing house.

The role will contribute to the transition from primarily descriptive analytics toward more advanced, data-driven decision making.

Skills & Experience

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, or a related field;
• 5+ years of experience in data science roles;
• Strong experience applying data science and machine learning to business problems, ideally in areas such as sales, marketing, customer behavior, demand forecasting, or pricing optimization;
• Proficient in Python and SQL for data analysis, scripting, and machine learning;
• Proficient in using agentic coding tools like Claude Code, Codex, Cursor
• Experience with SciKit-learn, Pytorch, and similar machine learning frameworks for building and deploying machine learning models;
• Experience working with modern data warehouses/lakehouses like Snowflake, Databricks, BigQuery, Redshift
• Strong analytical and problem-solving skills, with the ability to translate ambiguous business problems into data-driven solutions;
• Ability to work independently and collaborate with business and technical stakeholders;
• Fluent in English and excellent communication skills.

Nice to have: 

• Strong background in data science, with extensive experience in leveraging advanced analytics and machine learning to drive data-driven business decisions.

Responsibilities

• Design, develop, and implement advanced data models and machine learning algorithms to solve complex problems in the publishing domain, like author discovery;
• Analyze sales, marketing, customer, product, and pricing data to identify opportunities and support business decisions;
• Develop data-driven approaches to areas such as demand forecasting, customer behavior, sales optimization, marketing effectiveness, and pricing;
• Work with business stakeholders to understand broad or ambiguous business challenges and translate them into analytical and machine learning solutions;
• Collaborate with cross-functional teams to understand data requirements and deliver actionable insights and recommendations;
• Build and maintain scalable data pipelines using technologies such as Snowflake, and DBT;
• Leverage Python and SQL for data analysis, model development, experimentation, and automation;
• Utilize SciKit-learn, Pytorch and similar frameworks for developing and deploying machine learning models;
• Help evolve the organization from descriptive analytics toward predictive and prescriptive analytics and data-driven decision making;
• Stay current with emerging trends and technologies in data science and machine learning.

We are looking for an experienced Azure Data Architect to join a long-term European project. The project is planned for one year. 

The role focuses on designing and evolving enterprise data architecture in Azure, including the data layer supporting GenAI, RAG, and Agentic AI applications. This is an architecture-focused position — hands-on development of AI agents or RAG solutions is not required.

Responsibilities:

• Design and evolve scalable enterprise data architecture on Microsoft Azure.
• Own architectural decisions related to data modeling, ingestion, storage, integration, and modernization.
• Design data platforms and data layers supporting GenAI, RAG, and Agentic AI applications.
• Define approaches for preparing, storing, governing, and exposing enterprise data and knowledge for AI consumption and retrieval.
• Design solutions for both structured and unstructured data.
• Develop scalable metadata- and configuration-driven data ingestion approaches.
• Design and optimize Data Lake and Lakehouse architectures.
• Define architectural patterns and integrations across Azure data services.
• Ensure scalability, maintainability, security, and reliability of data-platform solutions.

• Collaborate with engineering and other technical teams on architecture implementation.

   

Requirements:

• Strong experience in enterprise Azure Data Architecture.
• Proven experience designing production data architecture supporting GenAI, RAG, or Agentic AI applications.
• Hands-on project experience designing or owning the data layer behind a production RAG/Agentic AI solution.
• Strong knowledge of Azure Cosmos DB — essential.
• Strong experience with Azure Synapse Analytics and Azure Databricks.
• Experience with Azure SQL Managed Instance, SQL Server, and T-SQL.
• Strong knowledge of Azure Data Lake and Lakehouse architecture.
• Experience with Azure Functions.
• Strong knowledge of data modeling, data ingestion, and data-platform modernization.
• Experience working with both structured and unstructured data.
• Experience designing metadata/configuration-driven ingestion and scalable data platforms.
• Understanding of data patterns used in GenAI/RAG solutions, such as document processing, metadata, chunking, embeddings, vector search, and retrieval.
• Experience taking ownership of architectural decisions in complex enterprise environments.

• Spoken English — B2 or higher.

   

We offer:

• Work schedule is flexible — fixed amount of hours that you need to work per month
• 20+ personal days for rest per year (10 days allocated every 6 months; unused days do not expire)
• Up to 12 official public holidays per year (each employee can decide how many to use)
• Birthday day off
• Reimbursement of 5 sick days per year
• Partial compensation for external courses/conferences (after the completion of the Adaptation Period)
• Partial compensation for external professional certifications
• Reimbursement for sports or massage
• Large library with a scheduled purchase of new books every half a year
• Yearly Individual Development Plan (after the completion of the Adaptation Period)

If your experience matches this role, we’d love to hear from you. Apply now!