Jobs Data Science

Workload: minimum 50%, up to 80–100% !!!
Start: after summer holiday period (early autumn)
Duration: long-term assignment (exact length to be confirmed)
Location: flexible / hybrid (EU-based collaboration expected)
English: B2


Description:
We are looking for an experienced Senior Data Architect to define a reusable and scalable data foundation supporting sustainability, EHS, and product compliance use cases within a global manufacturing environment.

This assignment focuses on building a governed data architecture that enables automation of lifecycle-related calculations and reporting (such as LCA, product carbon footprint, and environmental declarations), while also supporting broader sustainability reporting, regulatory compliance, and future digital product requirements.

Responsibilities:

• Define the target data architecture and reusable data foundation
• Identify and structure key data domains and data products
• Design data ownership and governance models
• Establish principles for:
• Data quality and validation
• Data lineage and traceability
• Versioning and auditability
• Ensure a modern lakehouse platform acts as the governed backbone for trusted data
• Enable integration of external calculation and authoring tools where appropriate
• Collaborate across business and IT domains to avoid fragmented point-to-point integrations
• Support the creation of reusable, auditable data products for multiple stakeholders

Required experience !!!!!:

• Strong experience in data architecture and modern data platforms (lakehouse)
• Hands-on knowledge of data governance, data products, and domain-driven data design
• Experience working with manufacturing, product data, or industrial environments
• Understanding of sustainability reporting and/or compliance-driven data requirements
• Ability to work across multiple stakeholders: business, IT, data, and compliance teams
• Experience integrating data across systems such as ERP, PLM, and analytics platforms

Nice to have:

• Experience with sustainability-related domains (e.g. lifecycle assessment, carbon footprint, environmental reporting)
• Experience with compliance-driven data (e.g. chemical, product, EHS)
• Familiarity with emerging requirements such as Digital Product Passport

We are looking for an experienced Senior Data Scientist to join our team and help unlock the full value of data across our platform, products, and business operations. In this role, you will apply advanced analytics, machine learning, and statistical modeling to generate actionable insights, improve decision-making, and drive innovation across the organization.

Responsibilities

• Analyze large, complex datasets to uncover trends, patterns, and insights that support strategic business and product decisions.
• Build predictive models to forecast business outcomes, improve operational efficiency, and support decision-making across multiple functions.
• Design and implement feature engineering techniques to improve machine learning model performance and accuracy.
• Partner with cross-functional teams including product, engineering, operations, and business stakeholders to identify opportunities and translate them into scalable data science solutions.
• Clean, preprocess, and structure data from multiple sources to ensure high-quality inputs for analysis and modeling.
• Develop, test, and deploy machine learning models for use cases such as classification, regression, clustering, recommendation systems, and forecasting.
• Evaluate and optimize model performance using appropriate statistical and machine learning metrics.
• Create dashboards, reports, and visualizations that clearly communicate findings and recommendations to technical and non-technical audiences.
• Automate recurring analysis, reporting, and model workflows to improve efficiency and consistency.
• Monitor production models and continuously improve performance, reliability, and business impact over time.
• Stay current with the latest advancements in data science, machine learning, and AI, and apply relevant innovations to PredictSpring’s platform and operations.

Requirements

• Excellent communication skills, including fluent verbal English, with the ability to explain complex concepts to non-technical stakeholders and collaborate effectively across teams.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• Proven experience as a Data Scientist, with a strong background in machine learning, statistical analysis, and predictive modeling.
• Strong programming skills in Python preferred, or similar languages such as R, with hands-on experience using libraries such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
• Expertise in building and deploying machine learning models for classification, regression, time-series forecasting, recommendation systems, and related applications.
• Strong experience with data wrangling, feature engineering, and working with structured and unstructured datasets.
• Proficiency in SQL for querying, transforming, and analyzing structured data.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud for model deployment and data workflows.
• Experience with data visualization tools such as Power BI, Tableau, or Python visualization libraries.
• Strong analytical thinking, problem-solving ability, and a passion for applying data science to real-world business challenges.

Preferred Qualifications

• Familiarity with big data and distributed processing tools such as Apache Spark, Hadoop, or Databricks.
• Experience with deep learning frameworks such as TensorFlow, Keras, or PyTorch.
• Experience with natural language processing techniques such as text classification, sentiment analysis, or large language model applications.
• Strong foundation in statistical analysis, experimentation, and hypothesis testing.
• Experience collaborating with or supporting data engineering teams in building scalable data pipelines.
• Familiarity with version control tools such as Git.
• Strong business acumen and the ability to align technical solutions with business goals.
• Experience in retail, e-commerce, omni-channel commerce, or POS technology is a strong plus.

Why PredictSpring?

• Join a market-leading company shaping the future of omni-channel retail and modern POS.
• Work on high-impact challenges at the intersection of commerce, data, and customer experience.
• Collaborate with a talented global team in a flexible remote work environment.
• Enjoy opportunities for growth, learning, and professional development.
• Contribute to products used by some of the world’s most recognized retail and lifestyle brands.
• Be part of an innovative, collaborative, and data-driven culture focused on delivering measurable business value.

Quantum is a global technology partner delivering high-end software products that address real-world problems. 

We advance emerging technologies for outside-the-box solutions. We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps, Blockchain, and more.

Here at Quantum, we are dedicated to creating state-of-the-art solutions that effectively address the pressing issues faced by businesses and the world. To date, our team of exceptional people has already helped many organisations globally attain technological leadership.

We constantly discover new ways to solve never-ending business challenges by adopting new technologies, even when there isn't yet a best practice. If you share our passion for problem-solving and making an impact, join us and enjoy getting to know our wealth of experience!

About the position

Quantum is expanding its team in Central Europe and is looking for talented Data Science Engineers to join us. Our projects span multiple domains, including data analysis, fintech, computer vision, image processing, edge-device solutions, Large Language Models (LLMs), and classical Machine Learning applications. We build custom Data Science solutions for clients across various industries, combining strong engineering practices with a research-driven mindset.

Joining Quantum means becoming part of a team that values solid technical fundamentals, continuous learning, and practical problem-solving. You'll collaborate on impactful products, work with cutting-edge technologies, and contribute to projects that turn complex ideas into real-world solutions.

Must have skills:

• 3+ years of commercial DS/ML experience
• Solid foundation in linear algebra, statistics, and probability
• Strong Python, including NumPy, Pandas, and scikit-learn
• Hands-on experience with PyTorch (or TensorFlow)
• Deep experience in at least one of: 
  • Computer Vision (modern DL: detection, segmentation, classification - ViT, YOLO, SAM); 
  • LLMs / NLP (fine-tuning, RAG, prompt engineering, embeddings, evaluation); 
  • Classical ML at scale (tabular, time series, recommender systems)
• Working knowledge of Transformers and attention; familiarity with CNNs
• Experience deploying models to production (Docker, REST/gRPC serving, basic monitoring)
• Experience with at least one cloud platform (AWS, GCP, or Azure)
• Clean code and Git workflow
• Experience with SQL
• Upper-Intermediate English (B2+) - you'll communicate directly with clients

Nice to have skills:

• Cross-domain exposure: if your main strength is CV, some LLM exposure is a plus (and vice versa)
• Edge deployment: TensorRT, OpenVINO, ONNX, quantisation, model distillation, mobile/embedded inference
• LLM tooling: LangChain/LlamaIndex, vector databases (pgvector, Pinecone, Weaviate, Qdrant), LoRA/QLoRA fine-tuning, agentic frameworks
• MLOps & model monitoring: MLflow, DVC, Weights & Biases, CI/CD for ML
• Classical CV with OpenCV (still relevant for hybrid pipelines and edge work)
• Ability to read recent papers and implement methods in new domains
• Experience working with external clients
• Participation in Kaggle competitions

Your tasks will include:

• Own full-cycle DS projects: scoping with the client, data prep, modelling, evaluation, deployment
• Build solutions across CV, LLM/NLP, and classical ML depending on the project pipeline
• Deploy models to production - cloud, edge, or hybrid, depending on client needs
• Read recent research and adapt methods to client problems
• Communicate technical decisions and trade-offs directly to clients

We offer:

• Delivering high-end software projects that address real-world problems
• Surrounding experts who are ready to move forward professionally
• Professional growth plan and team leader support
• Taking ownership of R&D and socially significant projects
• Participation in worldwide tech conferences and competitions
• Taking part in regular educational activities
• Being a part of a multicultural company with a fun and lighthearted atmosphere
• Working from anywhere with flexible working hours
• Paid vacation and sick leave days

Join Quantum and take a step toward your data-driven future.

Workload: minimum 50%, up to 80–100% !!!
Start: after summer holiday period (early autumn)
Duration: long-term assignment (exact length to be confirmed)
Location: flexible / hybrid (EU-based collaboration expected)
English: B2


Description:
We are looking for an experienced Senior Data Architect to define a reusable and scalable data foundation supporting sustainability, EHS, and product compliance use cases within a global manufacturing environment.

This assignment focuses on building a governed data architecture that enables automation of lifecycle-related calculations and reporting (such as LCA, product carbon footprint, and environmental declarations), while also supporting broader sustainability reporting, regulatory compliance, and future digital product requirements.

Responsibilities:

• Define the target data architecture and reusable data foundation
• Identify and structure key data domains and data products
• Design data ownership and governance models
• Establish principles for:
• Data quality and validation
• Data lineage and traceability
• Versioning and auditability
• Ensure a modern lakehouse platform acts as the governed backbone for trusted data
• Enable integration of external calculation and authoring tools where appropriate
• Collaborate across business and IT domains to avoid fragmented point-to-point integrations
• Support the creation of reusable, auditable data products for multiple stakeholders

Required experience !!!!!:

• Strong experience in data architecture and modern data platforms (lakehouse)
• Hands-on knowledge of data governance, data products, and domain-driven data design
• Experience working with manufacturing, product data, or industrial environments
• Understanding of sustainability reporting and/or compliance-driven data requirements
• Ability to work across multiple stakeholders: business, IT, data, and compliance teams
• Experience integrating data across systems such as ERP, PLM, and analytics platforms

Nice to have:

• Experience with sustainability-related domains (e.g. lifecycle assessment, carbon footprint, environmental reporting)
• Experience with compliance-driven data (e.g. chemical, product, EHS)
• Familiarity with emerging requirements such as Digital Product Passport

We are looking for a Computer Vision Engineer with strong experience in deep learning and production computer vision systems.

The role involves developing and bringing computer vision models into production, covering the full lifecycle from training and evaluation to deployment and system integration.

Responsibilities:

• Develop and improve Computer Vision and Machine Learning models
• Design and implement solutions for object detection, classification, segmentation, and tracking
• Work with large-scale image, video, and telemetry datasets
• Prepare, process, and maintain datasets for model training and evaluation
• Manage model training, validation, and testing workflows
• Optimize models for production deployment and real-time performance
• Integrate ML models into software services, applications, and APIs
• Analyze model performance and identify opportunities for quality improvement
• Participate in the design and architecture of AI components within the product ecosystem
• Collaborate closely with Backend, Infrastructure, Data, and Product Engineering teams
• Contribute to the development of MLOps practices and the end-to-end machine learning lifecycle.

Requirements:

• 3+ years of experience in computer vision
• High proficiency in Python
• Strong experience with deep learning and the PyTorch framework for computer vision tasks
• Research experience in computer vision with a focus on delivering results
• Ability to work independently or within a small team, with a strong sense of ownership over results

Nice to Have:

• Experience working with thermal imaging data (thermal cameras, infrared imagery) would be an advantage
• Experience with deep learning solutions for detection, tracking, image retrieval, and segmentation tasks
• Understanding of geometric computer vision principles
• Model optimization: quantization, pruning, neural network compilers
• Hands-on experience implementing low-level CV algorithms
• Experience with sensor fusion (IMU, magnetometer, GNSS, camera)
• Knowledge of C++

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)

We are looking for Computer Vision Engineers with strong experience in classical and geometric computer vision, and hands-on experience with SLAM, Visual-Inertial Odometry (VIO), or related localization systems.

We are open to candidates of different seniority levels (Junior to Senior), with responsibilities and scope defined by experience.

Responsibilities:

• Develop and optimize classical and geometric computer vision algorithms
• Work with feature tracking, matching, and geometric processing
• Contribute to SLAM / VIO pipeline components
• Integrate and test multi-sensor fusion systems (camera + IMU)
• Design and run experiments, evaluate algorithm performance
• Translate research papers into practical implementations
• Collaborate with cross-functional engineering teams

Required Qualifications:

• Hands-on experience with classical computer vision
• Understanding of geometric computer vision concepts, including camera models, feature detection, and tracking
• Familiarity with SLAM and/or Visual-Inertial Odometry (VIO) concepts
• Experience with C++ and Linux environments
• Ability to design, implement, and optimize computer vision algorithms in practice
• Ability to learn from and implement research-based methods
• Degree or ongoing studies in Computer Science, Mathematics, Physics, Engineering, or a related STEM field

Nice to Have:

• Experience with Python
• Knowledge of neural networks and CV libraries/frameworks (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
• Experience with sensor fusion techniques
• Familiarity with embedded or real-time systems
• Robotics or navigation background

Dataforest is looking for a Data Scientist to join an interesting software development project in the field of Cybersecurity. Our client's platform offers Identity Insights drives real-time, multi-contextual digital forensics to protect new account opening workflows and expose fake accounts already in a customer database.

    Required Qualifications

• 2+ years of experience working with large-scale, complex datasets.
• Experience with imbalanced data.
• High proficiency in Python for data analysis, feature engineering and modeling.
• Expertise in exploratory data analysis and preparing clean, structured datasets for model development.
• Hands-on experience with AI/ML techniques:
• Supervised (eg. gradient boosting, decision trees, etc.)
• Unsupervised (eg. anomaly detection, clustering, etc.)
• Familiarity with basic statistical concepts and model evaluation metrics (eg. precision, recall, ROC-AUC).
• Upper-intermediate (B2) or higher level of English.
  
  Nice to Have
• Hands-on experience in the fraud/risk domain.
• Experience with Databricks (including Pyspark) for data processing, experimentation, and model development.
• Experience in MLflow library for experiment tracking and model lifecycle management.
• Experience working with diverse data sources (e.g., behavioral, device, or transactional data) and deriving meaningful features.
• Experience assessing data quality and validating new data sources in production environments.

     Key Responsibilities

• Analyze large-scale transaction datasets to identify fraud patterns and risk signals.
• Develop and validate ML models for risk scoring and fraud detection/classification.
• Support deployment of models into production environments by collaborating with the development team.
• Monitor model performance, conduct regular evaluations, analyze the results.
• Perform feature engineering to continuously improve model performance.
• Collaborate with the client on R&D efforts, including exploratory data analysis, feature development, and testing new approaches.

     We offer

• Great networking opportunities with international clients, challenging tasks;
• Building interesting projects from scratch using new technologies;
• Personal and professional development opportunities;
• Competitive salary fixed in USD;
• Paid vacation and sick leaves;
• Flexible work schedule;
• Friendly working environment with minimal hierarchy;
• Team building activities and corporate events.

Are you a Data Scientist with a love of LLMs, generative AI?

We are looking for a passionate Data Scientist to implement AI solutions aimed at achieving business goals.

This role offers the opportunity to work on cutting-edge AI adoption projects that helps to improve current business processes.

Skills requirements:
• Strong Python Experience (1 year +);
• Experience with LLM , Diffusion models (1 year +);
• Knowledge of Prompt engineering;
• Experience with Gen AI-related technologies such as LangChain and RAG;
• Experience with Neural Networks (Optional) ;
• Experience with NLP , Predictive analytics and Machine learning;
• Experience with Pandas;
• Experience with SQL, including experience with large datasets;
• Strong experience in statistics;

Key responsibilities:
• Develop AI agents that utilize LLM, RAG and langchain approach;
• Implement LLM and Diffusion models to boost business productivity;
• Utilize LLM (LLM Vision) to improve object detection, text classification and extraction;
• Create forecasting, recommendation, and classification models;
• Transform business challenges to AI applications;

We offer:

• Great networking opportunities with international clients, challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary nominated in USD;

• Paid vacation and sick leaves;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

Domain: iGaming / Gambling
Format: Product company
Experience: 5+ years

About the Company

We are an international product company operating in the gambling sector. Our platform delivers real-time personalization for casino and sportsbook products using advanced machine learning. The solution processes live behavioral, transactional, and contextual data to improve player engagement, retention, and overall performance for operators worldwide.

Our focus is on building production-grade ML systems that directly influence what users see in real time — from game recommendations to personalized content and promotions.

Role Overview

We are looking for a Senior Data Scientist to join a product-focused team working on real-time personalization and recommendation systems for iGaming platforms.

This is a hands-on role that combines modeling, experimentation, and close collaboration with engineering and product teams in a high-load, real-time production environment.

Main Responsibilities

• Develop ML-driven features for casino products using supervised learning (regression, ranking, classification)
• Maintain and improve existing recommendation systems in production
• Enhance models using gradient boosting and other supervised approaches
• Perform data cleaning, preprocessing, and feature engineering
• Design and maintain pre- and post-processing workflows
• Optimize training and inference pipelines for performance and reliability
• Integrate ML models into Airflow pipelines in a multi-tenant environment
• Adapt and configure the solution for different clients (tenants)
• Collaborate closely with product and engineering teams on experimentation and feature delivery

As Part of the Team You Will

• Work cross-functionally with data scientists, engineers, product owners, designers, and researchers
• Analyze large-scale datasets to extract insights for product and business decisions
• Propose, implement, and evaluate ML approaches to solve real business problems
• Support and evolve a recommendation solution used across multiple tenants
• Influence product strategy through research, experimentation, and data-driven insights into user behavior

Experience & Education

• 5+ years of professional experience in data science
• Degree in a quantitative field (Mathematics, Statistics, Computer Science, or similar)

Core Skills

• Strong proficiency in Python and SQL
• Hands-on experience with data processing tools (Pandas, Polars)
• Solid engineering skills for building and maintaining scalable ML systems
• Experience implementing observability in ML pipelines (metrics, logging, alerting)
• Knowledge of Docker and Kubernetes
• Strong analytical mindset with the ability to solve loosely defined problems
• Hands-on experience with supervised ML techniques, including:
  • Regression and ranking models (XGBoost, LightGBM, CatBoost, neural networks)
  • Feature engineering and model evaluation (AUC, NDCG, MSE, uplift metrics)
  • Personalization or recommendation systems
• Proven experience deploying ML models to production (near real-time or batch)
• Solid understanding of statistical methods (A/B testing, significance testing)

Nice to Have

• Production experience with large-scale recommendation systems
• Experience with Airflow, Valkey/Redis, FastAPI in production
• Familiarity with contextual bandits or reinforcement learning
• Experience with AutoML tools

Team Summary

Our analytical teams provide actionable insights during the development and rollout of AI-driven features, including motion and object detection. We quantify user experience for core device functionality, conduct deep-dive studies to shape the product roadmap, and evaluate new initiatives from initial trials through full-scale production.

Job summary

We are looking for an experienced Data Analyst/Engineer to join our team. In this role, you will develop self-service dashboards, build data models, monitor key product features, and collaborate with cross-functional teams to drive impactful decisions. This role offers an opportunity to work with large datasets, optimise analytical processes, and influence product growth with meaningful data insights.

Responsibilities and Duties

• Build data models for covering analytics
• Develop self-service dashboards for stakeholders
• Use data to analyse user behaviour, turning insights into practical guidance for product development and strategy
• Create reports that present data outcomes to stakeholders, enabling them to make informed decisions
• Use AI agents to automate routine tasks and ad-hocs

Qualifications and Skills

• 4+ years of experience as a BI/Data Analyst or Data Engineer
• Hands-on experience with data warehousing and ETL pipelines
• Advanced knowledge of SQL
• Hands-on experience with AWS (Athena, Redshift)
• Good written and spoken English

Nice to have

• Experience with AI agents
• Computer science fundamentals
• Knowledge of Python
• Hands-on experience with QuickSight, Tableau or PowerBI
• Good knowledge of statistics and probability theory

We offer multiple benefits that include

• The environment of equal opportunities, transparent and value-based corporate culture and an individual approach to each team member
• Competitive salary packages with performance-based annual reviews
• Opportunity to receive a Performance Bonus for your individual achievements and a Loyalty Bonus recognizing your dedication to the company
• Employment via Contract of Employment (UoP) in complete alignment with Polish Labour Law
• Guaranteed paid vacation, public holidays, and medical leaves as per statutory regulations
• Continuous growth and development opportunities through internal knowledge hubs, corporate courses, and free English classes
• Comprehensive private medical insurance to supplement your standard NFZ coverage

We are looking for a Senior AI/ML Engineer to join our team!

Our client is an innovative technology division within one of the world's top-10 copper producers. The team focuses on leveraging AI, machine learning, and advanced analytics to optimize industrial operations, improve asset reliability, and support data-driven decision-making across global mining and production facilities. The role is focused on building intelligent solutions for predictive maintenance, anomaly detection, and asset performance optimization, helping reduce downtime and improve operational efficiency across large-scale industrial environments.

Responsibilities:

• Design, develop, and deploy machine learning models for predictive maintenance, anomaly detection, and asset health monitoring.
• Build and maintain production-grade ML pipelines for time-series forecasting and sensor/telemetry data processing.
• Collaborate with Data Engineers and Analytics Engineers on data preparation, feature engineering, and model integration.
• Integrate model outputs, risk scores, and predictive insights into operational dashboards and business applications.
• Establish and maintain MLOps processes, including model deployment, monitoring, retraining, and drift detection.
• Research and evaluate new AI/ML approaches, tools, and technologies to improve predictive capabilities and business outcomes.
• Work closely with business and technical stakeholders to translate complex analytical results into actionable recommendations.

Requirements:

• 5+ years of experience as a Machine Learning Engineer or Data Scientist.
• Strong Python skills and hands-on experience with Pandas, NumPy, Scikit-Learn, SciPy, and related ML libraries.
• Proven experience with time-series forecasting and predictive modeling techniques (ARIMA, Prophet, XGBoost, LSTM/RNN, etc.).
• Experience working with telemetry, IoT, sensor, or equipment performance data.
• Hands-on experience with Azure Machine Learning, Databricks, MLflow, or similar MLOps platforms.
• Strong SQL skills and experience working with both relational and non-relational databases.
• Experience building and deploying production-ready ML solutions.
• Strong analytical and problem-solving skills with the ability to translate technical insights into business value.

Nice to have:

• Master's or PhD degree in Data Science, Statistics, Engineering, Mathematics, Operations Research, or a related quantitative field.
• Experience in mining, manufacturing, heavy industry, utilities, or other asset-intensive domains.
• Knowledge of Operational Technology (OT) environments and reliability engineering concepts.
• Experience with enterprise asset management systems such as SAP PM or IBM Maximo.
• Familiarity with reliability methodologies such as RCM or FMEA.
• Experience with real-time data processing and anomaly detection on streaming platforms (Kafka, Azure Stream Analytics, etc.).

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

We are looking for a Middle Data Scientist (Computer Vision) to join our team and work on real-time intelligent systems operating in dynamic environments.

In this role, you will focus on developing and improving computer vision algorithms, working with image and video data, and building robust pipelines that perform reliably in real-world conditions. The position involves a mix of research and practical engineering, where you will experiment with different approaches, evaluate model performance, and contribute to the development of scalable, high-performance solutions.

This is a great opportunity for someone who enjoys solving complex problems, working with modern AI/ML technologies, and seeing their solutions applied in real systems.

THAT WOULD BE WONDERFUL IF YOU HAVE:

• 2+ years of experience in Computer Vision

• 2+ years of experience in Data Science / Machine Learning

• Strong Python skills

• Experience with any of the following: Google Cloud, AWS, Azure

• Hands-on experience with computer vision libraries

• Experience with deep learning frameworks (PyTorch or similar)

• Understanding of object tracking/detection approaches (classical + NN-based)

• Experience working with image/video data (preprocessing, dataset creation, augmentation)

• Solid understanding of model evaluation and benchmarking

• Hands-on experience with model optimization for edge deployment

• Understanding of real-time or near real-time systems

• Upper-intermediate english

WOULD BE A PLUS:

• Experience with C/C++ or Rust

• Experience with Linux-based systems

• Experience with SLAM

• Experience with robotics, control systems, or sensor-based systems

• Familiarity with edge devices (e.g., NVIDIA Jetson, Raspberry Pi)

• Experience with simulation environments

RESPONSIBILITIES:

• Research and implement image and video processing algorithms using both classical and deep learning approaches

• Benchmark and evaluate models across different scenarios and datasets

• Work with video data to create and refine datasets for training and validation

• Develop and improve processing pipelines for real-time performance

• Analyze system behavior in real-world and simulated scenarios to identify issues and improve performance

• Collaborate with engineering teams to integrate solutions into real-time systems

ADVANTAGES FOR A CANDIDATE:

• Stable and competitive salary;

• Legally compliant gig contract with official tax reporting and payment;

• Work in a cool & experienced team;

• Useful & exciting projects;

• Up to 26 Days Off per year at your convenience;

• Convenient office in Vinnytsia or an opportunity to work remotely;

• Corporate culture with maximum automation of processes;

• Review of working conditions and position based on performance, productivity and development in accordance with a skills assessment program

• Excellent opportunities and prospects for professional growth in a company with a 9-year history

Project description

As part of the AI transformation strategy, Kyivstar invests resources in the integration of GenAI/Speech technologies into internal processes and day-to-day tasks, but also uses gained experience to help partners and clients to receive maximum benefits from these technologies too.

One of the key directions of this strategy is the development of AI assistants and services for external partners and clients. To achieve this, company is looking for AI Engineer (Speech) - specialists in the field of GenAI and Speech Processing with deep ML/DL background and practical skills in developing AI assistants and voice bots.

Necessary skills

• 4+ years of experience in ML/DL with strong focus on STT/TTS
• Hands-on experience training and deploying models for various speech processing tasks (e.g., speech classification, speech-to-text, text-to-speech, and speaker diarization)
• Practical experience building AI applications using LLMs
• Strong Python skills with experience in writing scalable software modules
• Fundamental knowledge of  ML/DL theoretical concepts
• Familiarity with RESTful APIs and basic web development principles
• Proficient in version control (Git) and containerization tools (Docker)

Would be a plus

• Experience with real-time / low-latency speech systems
• Experience with distributed data processing and training in multi-node, multi-GPU environments
• Experience with LangChain, LangGraph, and FastAPI
• Experience with Azure/AWS
• Familiarity with PySpark for large-scale data processing
• Exposure to Data Science in the Telecom industry

Responsibilities

• Design, train, and optimize ASR and TTS models for production use
• Design and develop AI-powered assistants
• Fine-tune and optimize large-scale models for specific business needs
• Collaborate with DevOps team to deploy the solution

• Plan and manage ML projects, articulate methodologies, and communicate results and business impact to stakeholders and customers

   

Proposed:

• Working with huge amounts of data at the largest operator in Ukraine
• Hands on experience with Cloud technologies and tools
• Great diversity of tasks and projects to utilize your knowledge and skills; flexibility in tools and approaches
• Opportunity to grow within the team of talented data scientists

WHO WE ARE

We are Edge Solutions Lab, a team of engineers with a strong background in product development of edge solutions and data platforms. Our legacy is grounded in the successful execution of the Hivecell product. We're committed to helping companies implement their product strategies and turn data into real, measurable value.

WHO WE ARE LOOKING FOR

We are seeking an experienced Data Scientist to join an exciting project for our client, Flow — a forward-thinking company transforming the way people live, work, and connect. You will work on real-world data challenges at the intersection of edge computing and data platforms, turning complex, large-scale data into models and insights that directly shape Flow's digital ecosystem and drive measurable product value.

KEY RESPONSIBILITIES

• Design, develop, and deploy machine learning models and statistical solutions that address real business problems
• Collaborate with product, engineering, and domain teams to translate requirements into data-driven solutions
• Conduct exploratory data analysis and feature engineering on large, complex datasets
• Build and maintain scalable data pipelines to support model training, evaluation, and inference
• Define and track model performance metrics; monitor models in production and drive continuous improvement
• Communicate findings, methodologies, and results clearly to both technical and non-technical stakeholders

• Contribute to the team's data science best practices, tooling, and documentation

   

WHAT YOU BRING ALONG

• 4+ years of professional experience as a Data Scientist or in a similar role
• Strong proficiency in Python and core data science libraries (pandas, NumPy, scikit-learn, etc.)
• Solid understanding of machine learning algorithms, statistical modeling, and model evaluation techniques
• Experience with deep learning frameworks (TensorFlow or PyTorch) is expected at this level
• Hands-on experience deploying models to production environments (REST APIs, containerization, cloud platforms)
• Proficiency with SQL and working with relational or distributed data stores
• Familiarity with MLOps practices: experiment tracking, model versioning, monitoring (e.g., MLflow, Weights & Biases)
• Experience working with cloud platforms such as AWS, GCP, or Azure
• Practical experience leveraging AI-powered tools (e.g., GitHub Copilot, ChatGPT, or similar) to enhance productivity and accelerate development workflows
• Working knowledge of: graph databases (Memgraph, Neo4j, or similar); edge inference runtimes (ONNX Runtime, llama.cpp, ExecuTorch); gradient boosting frameworks (XGBoost, LightGBM, CatBoost); time-series analysis on IoT or sensor data streams; Snowflake and dbt-based analytics pipelines
• English proficiency at B2 level or higher — able to communicate effectively in a professional setting, both written and spoken

WILL BE A PLUS

• Experience with edge computing or IoT data streams
• Knowledge of time-series analysis and anomaly detection
• Familiarity with data orchestration tools (Airflow, Prefect, or similar)
• Contributions to open-source projects or published research
• Experience in a product-focused or startup environment

SOFT SKILLS

• Strong analytical thinking with a pragmatic, solution-oriented mindset
• Ability to work independently and take ownership of tasks end-to-end
• Clear and concise communication — able to explain complex concepts to non-technical audiences
• Collaborative attitude and comfort working in cross-functional teams
• Intellectual curiosity and a continuous drive to learn and improve
• Comfort with ambiguity and the ability to prioritize effectively in a fast-paced environment