Jobs Data Science

We are the creators of a new fintech era!

Our mission is to revolutionize the world by making blockchain technology accessible to everyone in everyday life. WhiteBIT is a global team of more than 1,500 professionals united by a shared vision of shaping the future.

We are building our own blockchain ecosystem to ensure maximum transparency and security for over 8 million users worldwide. Our cutting-edge solutions, rapid adaptation to market challenges, and technological excellence set us apart from traditional companies.

Our official partners include Juventus, FC Barcelona, Lifecell, FACEIT, and VISA.

Join us as an Quantitative Researcher. 

Requirements:

Education & Experience:

— MSc or PhD in a quantitative field; a live trading track record outweighs credentials

— 5+ years in quantitative research or trading at a top-tier HFT firm, market maker, systematic fund, or crypto-native market maker; exchange-side market-structure experience is a plus

— Hands-on experience with at least one TradFi asset class (FX, futures, equities) and / or equivalent crypto asset classes; both maker and taker strategies

Core Technical Skills:

— Advanced probability, statistics, time-series analysis, optimization; strict validation discipline (multiple testing, out-of-sample hygiene, live–sim parity)

— Market microstructure: order-book dynamics, queue position, fill probability, adverse selection and markouts, market impact

— Expert Python (NumPy, pandas/Polars, PyTorch); working C++ or Rust for latency-critical components

— Tick-data engineering at scale: columnar stores, cross-venue normalization, data-quality control

Market Knowledge:

— Crypto microstructure: CEX matching engines and fee schedules, perpetuals (funding, mark price, liquidation/ADL), cross-venue arbitrage, DEX/AMM basics

— TradFi microstructure: FX ECN mechanics (firm vs last-look liquidity, prime brokerage), listed futures; low-latency architecture (tick-to-trade path, colocation, exchange protocols)

— Inventory and hedging: quoting models of the Avellaneda–Stoikov class and extensions, multi-asset inventory optimization, hedging, settlement workflows, real-time risk limits and kill switches

Exchange Microstructure & Mechanism Design:

— Maker-taker economics and market-quality measurement: fee-tier and rebate architecture, per-segment elasticity, spread/depth/slippage/markout metrics, defenses against rebate farming and wash trading

— Liquidity program design: obligation-based schemes (two-sided quoting, presence at touch, minimum depth, uptime) and incentive-based schemes (tiered rebates, credit lines, connectivity benefits)

— Maker protection and flow segmentation: markout-based counterparty scoring, retail price improvement (RPI) order types, asymmetric speed bumps and latency floors, minimum quote life, self-match prevention

— Exchange P&L modeling: net fee capture, subsidy budget and payback, LP unit economics from onboarding to self-sufficiency

Mindset & Soft Skills:

— Owner mentality with direct P&L accountability; ships to production and makes honest kill decisions

— Clear written communication with traders, engineers, exchange management, and external LPs

— Compliance discipline across crypto and TradFi market-abuse regimes

Responsibilities:

Responsibilities — Liquidity Program:

— Design the program end-to-end: MM tiers, admission criteria, obligations (max spread, min depth, uptime, presence at touch), incentives, and graduation to subsidy-free self-sufficiency

— Optimize the fee schedule for net capture: taker tiers priced to measured elasticity by segment; maker rebates funded from taker fees; safeguards against tier gaming

— Design order-book mechanics for comfortable quoting: tick and lot sizing, post-only / iceberg / RPI order types, self-match prevention, minimum quote life, passive-liquidity protection options

— Build the toxic-flow framework: markout-based flow classification, counterparty scoring, continuous monitoring, access rules or surcharges for consistently toxic takers

— Own the program financial model and roadmap: subsidy budget with payback targets; phases bootstrap → organic profitability → self-sufficiency; a market-quality dashboard as the single source of truth

Responsibilities — Trading Desc:

— Own the strategy roadmap — crypto first, then TradFi FX and futures; design pricing, quoting, hedging, and execution as one portfolio

— Run end-to-end alpha research on tick/order-book, cross-venue, funding/basis, and on-chain data

— Design the inventory-aware hedging framework, portfolio risk limits, and parameter governance

— Partner with engineering on low-latency implementation; validate in high-fidelity simulation and canary deployments

— Own P&L attribution, TCA/markout analysis, and research standards

— Lead the TradFi FX entry research workstream (LSEG FX Spot Matching, Euronext FX). 

Working terms

Immerse yourself in Crypto & Web3:Master cutting-edge technologies and become an expert in the most innovative industry.

Work with the Fintech of the Future:

• Develop your skills in digital finance and shape the global market.

Take Your Professionalism to the Next Level:

• Gain unique experience and be part of global transformations.

Drive Innovations:

• Influence the industry and contribute to groundbreaking solutions.

Join a Strong Team:

• Collaborate with top experts worldwide and grow alongside the best.

Work-Life Balance & Well-being:

• Modern equipment.
• Comfortable working conditions, and an inspiring environment to help you thrive.
• 24 calendar days of paid leave.
• Additional days off for national holidays.

With us, you’ll dive into the world of unique blockchain technologies, reshape the crypto landscape, and become an innovator in your field. If you’re ready to take on challenges and join our dynamic team, apply now and start a new chapter in your career!

Let’s Build the Future Together!

The Data/Ingestion Engineer will design and implement scalable ingestion pipelines for high-volume structured and unstructured insurance documents, including PDFs, scans, emails, Word, Excel and PowerPoint files. 

The role includes OCR/document extraction, text cleaning and normalization, semantic chunking, metadata tagging, vector storage/RAG preparation, validation, monitoring and integration with downstream AI solutions.

• At least 7 years of experience as Data Engineer with Python and SQL
• At least 5 with AWS, the rest should be more or less but should be real experience that the candidate is able to talk about and give a concrete example/
• Must to have : 
  • Python
  • SQL
  • AWS
  • S3
  • Step Functions
  • CloudWatch
  • Data/document ingestion pipelines
  • Processing of unstructured documents:
  • PDF
  • scanned documents
  • Word
  • Excel
  • PowerPoint
  • emails
  • OCR / document extraction technologies
  • AWS Textract or equivalent
  • Connectors/integrations with sources such as:
  • SharePoint
  • email
  • Text cleaning and normalization
  • Metadata extraction/tagging
  • Automated error monitoring
  • Validation of OCR/extraction results
  • Git
  • CI/CD
  • Testing
  • Public-cloud data processing/document ingestion experience
  • Good to have :
  • Vector databases
  • RAG
  • Semantic chunking
  • Vector-storage schema design
  • Retrieval mechanisms
  • Azure
  • Databricks
  • AWS Textract specifically
  • Experience within insurance / financial services
  • Experience handling enterprise security and low-latency SLA requirements
• English Level C1
• Duration of the mission :  1 year

Python Developer (Data Integration / Webhooks)

Task: Build a lightweight Python application to ingest third-party webhook data into PostgreSQL for analytics and dashboarding.

Key Responsibilities:

• Develop a Python service to receive and handle incoming webhooks (~22 endpoints/requests).
• Design the database schema and related tables in PostgreSQL.

• Process and store incoming payloads efficiently to support downstream dashboard creation.

   

Requirements:

• Python (FastAPI / Flask / Asyncio)
• PostgreSQL (schema design, SQL, ORM/SQLAlchemy)
• Solid understanding of Webhooks, REST, and JSON payloads
• Docker (containerization & deployment)

About the role 

We're hiring two Senior Data Ingestion Engineers for a major client in the insurance sector. You'll design and implement scalable ingestion pipelines for high-volume structured and unstructured insurance documents: PDFs, scans, emails, Word, Excel and PowerPoint files. 

The pipelines feed downstream AI solutions. The work covers OCR and document extraction, text cleaning and normalisation, semantic chunking, metadata tagging, vector storage and RAG preparation, validation, and monitoring. 

What you'll do 

• Design and build scalable document-ingestion pipelines on AWS (S3, Step Functions, CloudWatch). 
• Process unstructured documents: PDFs, scanned documents, Word, Excel, PowerPoint and emails. 
• Implement OCR and document extraction with AWS Textract or equivalent tools, and validate the extraction results. 
• Build connectors and integrations with sources such as SharePoint and email. 
• Clean and normalise text, and extract and tag metadata. 
• Prepare data for RAG: semantic chunking, vector-storage schema design and retrieval. 
• Set up automated error monitoring, alerting and quality checks. 
• Integrate ingestion outputs with downstream AI solutions, following enterprise security and SLA requirements. 

Must-have 

• 7+ years of commercial experience as a Data Engineer with Python and SQL. 
• 5+ years of hands-on AWS experience, including S3, Step Functions and CloudWatch. 
• Proven experience building data and document ingestion pipelines in a public cloud. 
• Processing of unstructured documents: PDF, scanned documents, Word, Excel, PowerPoint and emails. 
• OCR and document extraction technologies (AWS Textract or equivalent), including validation of OCR and extraction results. 
• Connectors and integrations with sources such as SharePoint and email. 
• Text cleaning and normalisation, and metadata extraction and tagging. 
• Automated error monitoring for data pipelines. 
• Git, CI/CD and testing practices. 
• English at C1 level. 

For every skill above, you should be able to give concrete examples from real projects. 

Nice to have 

• Vector databases, RAG, semantic chunking, vector-storage schema design and retrieval mechanisms 
• AWS Textract specifically 
• Azure and/or Databricks 
• Experience in insurance or financial services 
• Experience with enterprise security and low-latency SLA requirements 

Location 

Fully remote, but you must live in an EU member country and hold a valid residence permit there.  

What we offer 

• A 1-year full-time engagement with a major enterprise client 
• The option of a direct contract with the client (the details of the cooperation model are discussed individually) 
• Hands-on work at the intersection of document processing, data engineering and GenAI 
• Fully remote work within the EU 

How to apply 

Please send a CV tailored to this role. The client screens CVs strictly and won't review a generic CV or a list of keywords. For each relevant project, please include: 

• start and end dates, the context, and your personal role and responsibilities 
• the AWS services and tools you used (S3, Step Functions, CloudWatch, Textract and so on) and how you used them 
• the document types you processed, how you did the OCR, extraction, cleaning, metadata tagging and validation, and which sources you integrated (SharePoint, email) 
• any experience with RAG, vector databases, chunking or retrieval, plus your Azure, Databricks and insurance or financial-services experience 

Please also include: 

• your expected hourly rate (USD) 
• your English level 
• years of experience 
• your country of residence and residence status 
• your citizenship 
• your availability date 

N-iX is for a Middle Applied Scientist to join our team and improve how customers discover, evaluate, and select content for AI training datasets. You will own scoped scientific projects from problem framing through recommendation, while helping shape broader methods and standards with senior and principal data science colleagues. Working with product and engineering partners, you will turn evaluation results and experimental evidence into improvements to the Data Licensing platform.

This role is well suited to someone who has applied statistical and machine-learning methods in production and is ready to take greater ownership of product-facing scientific work.
 

Our customer is a technology company that powers one of the world's largest two-sided marketplaces for high-quality photos, illustrations, videos and music used by individuals, businesses, marketing agencies and media organizations of all sizes. In this role, you will be working with highly motivated and talented data scientists and engineers who are primarily focused on developing next-generation AI/ML systems that transform the way people find content they enjoy.
 

Responsibilities:

• Partner with senior and principal data scientists to improve dataset discovery, qualification, and selection by evaluating and enhancing retrieval, classification, filtering, and ranking approaches
• Develop and apply evaluation and sampling methods to measure dataset relevance, coverage, diversity, composition, and representativeness.
• Evaluate automated dataset-curation workflows, using structured error analysis to assess interpretation, selection quality, and failure modes and recommend improvements.
• Design and analyse experiments using offline evaluation and product telemetry to recommend improvements to curation quality, workflow performance, and customer experience.
   

Requirements:

• 4+ years of commercial experience in data science, applied science, machine learning, or a related field.
• Strong grounding in statistics, experimental design, and quantitative problem-solving.
• Experience evaluating search, recommendation, ranking, and similar machine-learning systems.
• Experience taking experiments from problem framing and metric definition through analysis and recommendation.
• Proficiency in Python and SQL and experience working with large datasets.
• Practical experience applying several relevant techniques, such as sampling, clustering, classification, optimisation, uncertainty estimation, or Bayesian methods.
• Experience using structured error analysis to identify opportunities to improve model or platform performance.
• Strong communication skills and experience working with product and engineering partners.
• Ability to innovate and identify new approaches to improve current practices.
• English level - upper-intermediate or higher
• Working experience AWS and/or GCP

Nice to have:

• Experience with embedding models, semantic search, information retrieval, and multimodal content.
• Experience evaluating LLM-based or agentic workflows.
• Understanding of annotation workflows, from human labelling to model-assisted and VLM-based annotation.
• Experience estimating full-population quality from representative samples.

Mine Marketing works on the connection between advertising, data, and automation. We’re looking for a Technical Data & Automation Specialist to join our team and work closely with leadership on data, automation, system development, troubleshooting, and production operations.


What you will do with us:
- Connect advertising systems with internal data systems
- Build and improve pipelines that handle bulk in real time 
- Dig deep into performance issues and translate data into business decisions 

What we're looking for 🎯
- Hands-on experience with Claude Code and building automations
-High command of SQL: complex queries, optimization, performance thinking 
- Understanding of Data Pipelines, ETL, and Data Processing Processes
- Familiarity with performance metrics: ROI, CPA, CTR and the ability to connect data to decisions
- Analytical, entrepreneurial thinking, and true independence in complex tasks

Significant Advantage
- Experience in production systems in the advertising / performance worlds
- Working with Meta Ads/Google Ads (APIs)
- AWS/GCP experience

What awaits you ✨
- Real data that drives business decisions
- Real technical challenges: scale, reliability, accuracy 
- Lots of ownership and freedom to move things fast


What we offer:
- Opportunities for professional development and personal growth 🚀

- Competitive salary, reasonable and fair working conditions 💵

- A ridiculously awesome team and work environment 🎉

- Training opportunities, including paid courses and webinars 💻

- Remote working conditions 🏠

- Generous PTO and Holidays 🌴

Join us and let's make some social media magic happen! Apply now!

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.

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 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)

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.