Jobs Data Science

Fozzy Group is one of the largest trade industrial groups in Ukraine and one of the leading Ukrainian retailers, with over 700 outlets all around the country. It is also engaged in e-commerce, food processing & production, agricultural business, parcel delivery, logistics and banking.
 

The Foodtech team is looking for a Data Scientist to develop the Operational Analytics function for a fast growing food delivery business. In this role, you will focus on time series forecasting, regression modeling, simulation modeling, and end-to-end machine learning pipelines to support resource planning and operational decision-making.

You will be responsible for developing simulation-based models that serve as a foundation for a digital twin of operational processes, enabling scenario analysis, stress testing, and what-if simulations for capacity planning and operational optimization.

You will work closely with product, engineering, and operations teams to transform data into measurable business impact through production-ready ML and simulation solutions.
 

Job Responsibilities:

• Develop and implement time series forecasting models for resource planning (demand, capacity, couriers, delivery slots, operational load);
• Build regression and machine learning models to explain key drivers and support operational decisions;
• Apply a wide range of time series approaches from classical models (SARIMA, ETS, Prophet) and ML models (GB) to modern Deep Learning models (LSTM, Temporal CNNs, Transformers for TS);
• Design, build, and maintain end-to-end automated ML pipelines, deploy and operate models in production using AWS SageMaker;
• Orchestrate training and inference workflows with Apache Airflow;
• Analyze large-scale operational datasets and convert results into insights, forecasts, and actionable recommendations;
• Collaborate with product managers, engineers, and operations teams to define business problems and validate analytical solutions;
• Monitor model performance, forecast stability, and business impact over time.
   

Requirements:

• Bachelor’s Degree in Mathematics / Engineering / Computer Sciences / Quantitative Economics / Econometrics;
• Strong mathematical background in Linear algebra, Probability, Statistics & Optimization Techniques;
• At least 2 years working experience on Data Science;
• Experience of the full cycle of model implementation (data collection, model training and evaluation, model deployment and monitoring);
• Ability to work independently, proactively, and to decompose complex problems into actionable tasks.
   

Skills:

• Strong proficiency in Python with solid application of object-oriented programming (OOP) principles (modular design, reusable components, maintainable code);
• Solid experience in time series forecasting and regression modeling;
• Practical knowledge of:o Classical and ML forecasting techniques;
  o Statistical methods (hypothesis testing, confidence intervals, A/B testing);
• Advanced SQL skills (window functions, complex queries);
• Experience building automated ML pipelines;
• Understanding of MLOps principles (model versioning, monitoring, CI/CD for ML).
   

Nice to have:

• Hands-on experience with AWS SageMaker (training jobs, endpoints, model registry);
• Experience with Apache Airflow for data and ML workflow orchestration;
• Knowledge of Reporting and Business Intelligence Software (Power BI, Tableau);
• Experience working with large-scale production data systems.
   

What We Offer:

• Competitive salary;
• Professional & personal development opportunities;
• Being part of dynamic team of young & ambitious professionals;
• Corporate discounts for sport clubs and language courses;
• Medical insurance package.

Evowill is looking for a Data Science Mentor to join our team. If you’re excited to share your knowledge with beginners in data science and machine learning, and enjoy teaching or want to try yourself in this role, we would be happy to collaborate!

You are:

• A Data Scientist/Data Analyst with 3–5+ years of experience in Data Science, Machine Learning, or Data Analytics;
• Patient, responsible, and well-organized;
• Interested in teaching and knowledge sharing;
• Curious and eager to learn, just as much as to teach;
• Proficient in writing clean, readable, and reproducible code;
• Passionate about helping others grow technically and intellectually;

• Comfortable working remotely with a flexible schedule (Ukrainian timezone).

   

We are:

• A Ukrainian-Colombian team;
• Working with Python, Data Science, and AI-related projects;
• Supported by experienced mentors who will help you onboard;

• Focused on growth, learning, and continuous improvement.

   

Technical skills:

• Strong proficiency in Python for data analysis;
• Hands-on experience with NumPy, Pandas, and Scikit-learn;
• Experience with both structured and unstructured data
• Solid understanding of machine learning concepts (classification, regression, clustering);
• Knowledge of statistics, basic and modern modeling techniques;
• Experience with Jupyter Notebooks or similar tools;
• Data handling skills: cleaning, preprocessing, and visualization (Matplotlib, Seaborn, or similar);
• Experience working with databases (SQL/NoSQL);
• Experience with XGBoost and Deep Learning models
• Experience with deep learning frameworks (TensorFlow, PyTorch, Keras);
• Familiarity with big data tools (e.g., Spark, BigQuery).
• Experience in NLP tasks such as topic modeling
• Understanding of embeddings, vector databases, and language models

• English — Upper-Intermediate or higher.

   

Nice to have:

• Experience with Git;
• Basic understanding of MLOps is a plus;
• Experience with cloud platforms (AWS, GCP, Azure);
• Experience deploying ML models;

We offer:

• Remote and flexible work;
• An international team (Ukraine + Colombia);
• Part-time opportunity;
• Professional growth;
• A supportive and collaborative environment.

Role overview

Partner with sales and delivery to win new data engagements. You'll translate vague client problems into credible, costed solution architectures, lead technical discovery, and present to stakeholders ranging from CTOs to procurement.

Responsibilities

• Lead technical discovery calls; turn business needs into reference architectures and high-level designs
• Build proposals, SoWs, and effort estimates jointly with delivery leads
• Run solution demos, POCs, and architecture walkthroughs for prospects
• Respond to RFPs/RFIs with clear technical narratives
• Stay current on the modern data stack and competitor offerings; advise sales on positioning and trade-offs

Required experience

• 5+ years in data engineering / data architecture, with at least 2 years in a client-facing or presale capacity
• Strong command of cloud data platforms across AWS, Azure, and GCP (at least two hands-on)
• Working knowledge of the major data warehouses and lakehouses: Snowflake, Databricks, BigQuery, Redshift
• Solid grasp of streaming (Kafka, Kinesis), orchestration (Airflow, dbt, Dagster, Prefect), and table formats (Delta, Iceberg)
• Comfortable estimating cost, effort, and risk across architectures you haven't personally built
• Excellent written and spoken English; able to lead a room of senior stakeholders

Nice to have

• Background in BI tooling (Power BI, Tableau, Superset)
• Experience with regulated industries (banking, insurance, healthcare)
• Certifications across two or more cloud/data vendors

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.

We are looking for a Computer Vision Engineer with solid ML/DL experience to join our team on challenging projects.
We consider engineers at Middle and Senior levels - tasks and responsibilities will be adjusted accordingly. 

Required Qualifications:

• 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 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 seeking an experienced Mid/Mid+ Data Scientist with expertise in Large Language Models (LLMs) such as GPT, Claude, and related technologies. The ideal candidate will have a strong background in natural language processing (NLP), machine learning, and deep learning models. They will play a critical role in developing and deploying cutting-edge LLM applications to drive innovation across our product lines.
 

Responsibilities:

• 5+ years of commercial experience as a Data Science / AI Engineer
• Strong Python skills and solid software engineering fundamentals
• Proven experience building high-load, production-grade systems
• 2+ years of experience working with LLM and NLP-related tasks
• Hands-on experience with RAG pipelines and vector databases
• Strong understanding of modern deep learning architectures
• Experience with at least one deep learning framework (TensorFlow or PyTorch)
• Experience with SQL and NoSQL databases
• Good knowledge of Kubernetes
• Experience working with modern AI development tools (e.g., Claude Code, Cursor)
• Familiarity with Model Context Protocol (MCP)
• Experience with production LLM frameworks (e.g., vLLM)
• Experience training or fine-tuning LLMs
• Experience with cloud platforms (AWS, Google Cloud, Azure)
• Participation in Kaggle or similar competitions
• Ukrainian Native, English B2

Role Overview

We are a systematic prop trading firm operating at the intersection of CeFi and DeFi, with infrastructure deployed across 50+ exchanges and 20+ chains.
 

We are looking for a Senior Quantitative Researcher & Algorithmic Strategist to join the trading team. In this role, you will fully own the lifecycle of trading strategies — from research and backtesting to production deployment and optimisation.
 

This is a high-autonomy, high-impact position with direct collaboration with the founding team.
 

Key ResponsibilitiesStrategy Development

• Develop proprietary alpha signals or adapt existing strategies
• Design, backtest, and forward-test systematic trading strategies
• Conduct statistical validation (walk-forward, out-of-sample, regime analysis)
• Analyse capacity, decay, and correlation within the portfolio
• Prepare research documentation and performance reports
   

Engineering & Deployment

• Translate research into production-grade code (Python / C++ / Rust)
• Build algorithms for CEX market-making programs (Binance, OKX, Bybit)
• Improve order book logic (spread, inventory, execution efficiency)
• Integrate strategies into low-latency infrastructure
• Monitor live performance and conduct post-trade analysis
   

Market Microstructure & Execution

• Optimize fill rates, slippage, and latency
• Work with order book dynamics and execution logic
• Improve rebate capture and maker program performance
   

RequirementsHard Requirements (Must-have)

• Proven live trading track record (real P&L, not only backtests)
• Strong knowledge of crypto market microstructure
• Production-level coding in Python
• Working knowledge of C++ or Rust (preferred)
• Strong quantitative background (statistics, probability, time-series)
• Experience with exchange APIs (REST/WebSocket)
• Ability to own strategies end-to-end independently
   

Nice to Have

• Experience in prop trading / HFT / crypto quant firms
• Market-making algorithm experience
• Experience with CEX maker programs
• Familiarity with DEX / on-chain trading / MEV
• Experience in arbitrage strategies (CeFi–DeFi / cross-venue)
• Risk management systems (PnL limits, volatility sizing)
   

Academic Background

• Degree in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or similar
• Practical track record is prioritized over formal education
   

What We’re Looking For

• Strong ownership mindset over strategies and results
• Ability to explain and defend your edge
• Deep understanding of why strategies work (and fail)
• Attention to execution details (fees, latency, fills)
• Intellectual honesty and data-driven thinking
• Collaborative, non-ego-driven approach
   

Compensation

• Base Salary: Competitive (USD / stablecoin)
• Performance Bonus: P&L-based allocation (high-water mark model)
• Capital Allocation: Up to $100M+ per strategy (based on performance)
• Infrastructure: Full access to trading stack (50+ venues, low latency)
• Format: Remote-first, high autonomy
   

What We Offer

• Ready-to-use trading infrastructure (no need to build from scratch)
• Direct access to decision-makers
• Fast capital deployment
• Exposure to cutting-edge crypto markets (CEX + DEX)
• Collaborative research environment
• Flat team structure
   

Hiring Process

1. Call with Recruiter (30 min) — background and strategy discussion
2. Team interview (60 min) — strategy walkthrough
3. Final C-level Interview (30 min) 

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

Join PwC's Data & AI team and help design and deliver the AI and machine learning solutions that drive real business impact. We're growing quickly due to a strong pipeline of client work, and we're hiring across multiple seniority levels — from junior to senior Data Scientists.

Python is the core skill we expect. Depending on your strengths, you may focus on machine learning, statistical modelling, NLP, computer vision, or GenAI. Many roles also include "full-solver" flexibility — contributing where needed, including experimentation, prototyping, deploying models, or working end-to-end on AI use cases using modern platforms (including Microsoft technologies where relevant).

What You'll Do:

• Build AI That Solves Real Problems: Design, develop, train, and evaluate machine learning and statistical models across a wide range of business challenges.
• Turn Messy Data Into Insights: Explore, analyse, and visualize complex datasets to uncover patterns that matter. Perform feature engineering, data preprocessing, and selection to maximize model performance.
• Push the Boundaries With GenAI & NLP: Design and implement solutions leveraging Large Language Models, Retrieval-Augmented Generation (RAG), and NLP techniques.
• Experiment Rigorously, Deploy Confidently: Collaborate with data engineers and platform teams to move models from notebook to production, monitor performance over time, and support continuous retraining and improvement.
• Work Directly With Clients: Collaborate with clients across Western Europe and the USA to understand their business challenges, frame problems as data science opportunities, and communicate findings clearly. 
• Stay Ahead of the Curve: Keep up with the latest in AI/ML research, emerging techniques, and new tools. 

Who We're Looking For:

• Programming Skills (Key Requirement): Strong programming skills in Python (e.g. scikit-learn, TensorFlow, PyTorch, pandas, NumPy, Hugging Face, LangChain). The ability to write clean, maintainable, and reproducible code is essential.
• Machine Learning: Demonstrated hands-on experience building, training, and evaluating ML models. Strong understanding of supervised and unsupervised learning techniques, model selection, hyperparameter tuning, and cross-validation.
• Statistics & Mathematics: Understanding of core statistical concepts, probability, and linear algebra.
• NLP & GenAI (Highly Valued): Experience with natural language processing, text analytics, large language models, prompt engineering, RAG architectures, or other GenAI techniques.
• Computer Vision (Nice to Have): Experience with image processing, object detection, visual reasoning, or satellite imagery analysis is an advantage.
• Data Handling: Proficiency in SQL and experience with data wrangling, cleaning, and transformation.
• Cloud & MLOps (Nice to Have): Experience with cloud platforms (preferably Azure: Databricks, Azure ML, Synapse) or similar services on AWS/GCP is an advantage.
• Professional Background: At least 2–3 years of professional experience in data science, machine learning, applied research, or similar analytical roles.
• Language Skills: English at B2 level or higher.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

About the role

We are looking for a Senior Data Scientist to lead the evolution of machine learning systems within a high-scale AdTech ecosystem.

This is not a “campaign optimization” role. You will work on the core decision-making systems (DSP level) — where pricing, bidding, pacing, and experimentation interact in real time across billions of events per day.

You will be shaping the “brain” of the platform: a set of interconnected systems where small improvements can have a large business impact.

What you’ll work on

• Pricing & Budget Scalability
  Scale budgets while maintaining performance and controlling overspend
• User Selection Optimization
  Improve CVR through smarter targeting and traffic selection
• Exploration Efficiency
  Reduce wasted spend while preserving learning
• Incrementality Measurement
  Measure true lift vs attributed performance
• Fraud Detection & Filtering
  Improve traffic quality and filtering strategies

What we expect from you

System-level thinking

• Ability to reason about interacting systems, not isolated models
• Understanding of:
  • auction dynamics
  • bidding vs pacing trade-offs
  • feedback loops between models
• Seeing problems beyond segmentation or heuristics

Strong experimentation mindset

• Designing experiments, not just running A/B tests
• Experience with:
  • metric design (proxy vs north star)
  • online vs offline evaluation gaps
  • interference and auction effects
• Ability to translate system changes into measurable impact

Ownership & impact

• Proven track record of driving business impact, not only building models
• Ability to explain:
  • expected vs actual impact
  • why results differ
• Performance accountability mindset

AdTech domain understanding

• Solid understanding of:
  • targeting vs bidding vs supply dynamics
• Experience working close to DSP / auctions/pricing systems

Collaboration maturity

• Ability to work across DS, MLE, and Product
• Understanding trade-offs and constraints
• Experience making decisions in ambiguous environments

Core responsibilities

• Turn ambiguous problems into testable hypotheses
• Design and run offline analysis + online experiments
• Use intermediate metrics to understand system behavior
• Build prototypes and iterate quickly
• Identify where system-level improvements are required
• Collaborate across teams to drive end-to-end impact

Requirements

• 5+ years in Data Science / Machine Learning
• Strong experience in high-frequency systems (AdTech / FinTech / similar)
• Python & SQL proficiency
• Experience with big data tools (Spark, Snowflake, etc.)
• Strong ML background (TensorFlow, PyTorch, or similar)
• Solid foundation in:
  • probability
  • statistics (frequentist / Bayesian)
  • causal inference
• Master’s or PhD in a quantitative field

Nice to have

• Experience with DSP / auctions / pricing systems
• Experience with large-scale experimentation

Position Overview

We are seeking an experienced Data Scientist/ML Engineer specializing in neural networks, with 3+ years experience in the applied field. The ideal candidate should be a great mentor and team player; python ninja with a strong background in various neural network architectures (recurrent, convolutional, feedforward, etc.) and a deep understanding of developing, tuning, and deploying different architectures. This role also requires excellent Python programming skills and a solid foundation in data analysis and statistics. If you strive in a fast pace environment, with tight deadlines but fast professional growth, you are welcome in our team!

Key Responsibilities:

• Create statistical summaries to support hypothesis testing and data-driven decisions during EDA
• Implement data preparation and feature engineering pipelines for the models
• Plan and implement algorithms for predictive modeling.
• Provide continuous improvement of models in production
• Lead the ML-driven python coding for end to end model deliveries, support our ML-related libraries/
• Collaborate with a cross-functional team of specialists, including senior and junior data scientists, Python developers and ML engineers, data analysts, and DevOps specialists.
• Provide expertise in tuning loss functions, metrics, sample weights adjustment, hyperparameter tuning and model improvement in general.
• Generate detailed evaluation reports, summarizing key findings and presenting actionable insights to stakeholders.
• Keep up with tight deadlines, agile environment of work with evolving objectives and KPIs, having the highest level of organisation and self management to provide a full work clarity, extensive tracking and documentation of your work.

Required Skills and Qualifications:

• Minimum of 3 years of professional experience as a Data Scientist or Machine Learning Engineer.
• Proficient in building custom neural networks using PyTorch.
• Strong experience with various neural network architectures specialised for time-series modelling and tabular data predictive modelling 
• Proficiency with neural network layers (like LSTM, GRU, Conv1D, Dense, Dropout, BatchNormalization) and activation functions (ReLU, Sigmoid, Tanh, Softmax).
• Experience with time series data, including loading, cleaning, and feature engineering using libraries like pandas, numpy. Knowledge of Darts library would be a large bonus.
• Expertise in model development, including selecting and developing models from the Darts library and building custom neural network architectures.
• In-depth knowledge of Python programming and relevant libraries (e.g., Scikit-learn, Pandas, PyTorch, Shap). We want to emphasize this requirement of excellency in python, including good working OOP knowledge. We do noе accept candidates with partial experience in python, as our projects require solid programming skills for writing and supporting data science related functionalities and libraries
• Solid understanding of statistics and data analysis.
• Skilled in using and tuning loss functions such as MSE, MAE, Cross-Entropy Loss, and custom loss functions relevant to time series forecasting.
• Experience with hyperparameter optimization using libraries like Optuna or Hyperopt.
• Capable of implementing and optimizing training loops in PyTorch, including data loaders and training validation steps.
• Knowledge of time series-specific cross-validation techniques and regularization methods to prevent overfitting.
• Strong skills in evaluating model performance using metrics like MSE, RMSE, MAE, MAPE, and R-squared.
• Familiarity with backtesting functionalities for validating model performance.
• Experience in model deployment, including serialization and deployment of models for real-time services.
• Strong communication skills for presenting findings and progress to stakeholders, using visualizations created with matplotlib, seaborn, or plotly.
• Proficiency in using Git for version control and collaboration.
• Major education in Data Science, Computer Science, or a related field IS A MUST. We do not accept people with other backgrounds.
• Certifications in deep learning are preferred.
• Excellent command of spoken and written English.
• Strong self-management, time management, and organizational skills.

• Ability to work under a structured management system while independently handling creative tasks.

   

What We Offer:

• Competitive remuneration package.
• Bonuses
• Professional mentorship and guidance from experienced team members.
• Opportunities for professional growth and continuous learning.
• A dynamic and collaborative work environment.
   

About DataObrii
DataObrii is a high-tech consulting firm specializing in data science, machine learning, and AI-augmented Internet of Things. Our team comprises experienced data scientists, python engineers, devops, hardware electrical engineers, and business analysts dedicated to delivering innovative, data-driven solutions that enhance business intelligence and efficiency. We emphasize continuous improvement, keeping up with current and emerging technologies, and delivering complete timely, effective solutions.

Our Values:

• Efficiency: We employ an agile approach to ensure timely delivery of high-quality solutions. This governs fast delivery cycles, quick and efficient solutions, iteratively going from PoC developments to fully enhanced production systems.
• Professionalism: Our commitment to excellence drives us to achieve success for our clients. This includes both technical and ethical proficiency required from all our employees.
• Creativity: We utilize design thinking to develop innovative solutions that address complex business challenges.
• Care: We invest time in understanding our clients' business models to provide tailored solutions that align with their objectives.
   

About The Role

As a Senior/Lead Software Engineer in our Machine Learning department, you will take ownership of high-impact initiatives that drive product quality, monetization, and user experience. You’ll apply your expertise in Python, data analysis, and modern AI tools to build, deploy, and optimize ML solutions end-to-end. This is a hands-on technical role that blends data science and engineering to deliver measurable business outcomes. You’ll collaborate closely with cross-functional stakeholders and contribute to evolving areas such as LLMs, Generative AI, and ML infrastructure. The role offers exposure to complex data challenges and the opportunity to shape Pearl’s AI-driven capabilities.

What You’ll Do

• Build, train, and deploy ML models that improve product performance and monetization.
• Collaborate with data, product, and engineering teams across multiple internal initiatives.
• Design and implement data pipelines for extraction, transformation, and analysis.
• Apply statistical and machine learning techniques to real-world business problems.
• Work on projects involving LLMs and Generative AI technologies.
• Analyze large datasets to identify trends, insights, and optimization opportunities.
• Integrate ML models into production systems and monitor their performance.
• Communicate findings and recommendations clearly to technical and non-technical stakeholders.
• Experiment with emerging AI tools and methodologies to enhance existing workflows.
• Ensure data quality, reliability, and scalability in all deliverables.

What We’re Looking For

• 3+ years of hands-on experience in ML Engineering or Data Science.
• 5-6+ years total experience in software or data engineering.
• Strong programming skills in Python.
• Proficiency in SQL for data querying and analysis.
• Solid understanding of data processing, analysis, and visualization.
• Experience with LLMs / Generative AI tools (e.g., OpenAI, Copilot, Cursor).
• Ability to build and deploy ML models end-to-end.
• Strong analytical and problem-solving mindset.
• Experience with .NET for integration work
• Upper-intermediate English proficiency (B2 or higher).
• Familiarity with Databricks or similar data platforms (nice-to-have).
• Exposure to AWS or other cloud-based ML environments (nice-to-have).

Why Join Us?

• High-Impact Data — Work with vast datasets generated by over a million daily visits, uncovering valuable insights.
• Collaborative Analytics Team — Join a team of 30+ skilled analysts who actively share knowledge and support each other.
• Cutting-Edge Tools & Techniques — Get hands-on experience with ML, Bayesian methods, and LLMs to solve real business challenges.
• Data-Driven Culture — Thrive in an environment where data informs every decision and drives continuous improvement.

Requirements: 
Address data is a central component of many processes within Westnetz. It is required for numerous applications, such as the installation of electricity meters, the connection of gas pipes, the billing of services or the deployment of technicians in the field.
Different types of address data are required depending on the use case. As part of a centrally managed expansion project, the address data system to be used by Westnetz for all central IT systems in future is to be fundamentally expanded. The main objective is to expand the address data repository with an additional address data pool in order to supply the required address data to the consuming systems.
In addition, enhancements will be implemented to make the system more user-friendly.

As part of the expansion of an address data master, the following services are to be provided:
- Performing the matching of various address data pools (geodata and attribute data) by developing a matching algorithm with adjustable thresholds
- Carrying out test management: creating test cases, executing the test cases, documenting the test results
- Documenting the interface tests
- Carrying out address data analyses and processing on Azure in SQL, Python and Spark to determine the quality of the address data

Profile:
- A degree in Computer Science, Business Informatics, Industrial Engineering or a related field
- Professional experience as a Data Scientist or in a similar role
- In-depth knowledge of Python, SQL and Spark
- Analytical thinking, structured approach to work

 

We're an R&D team working on autonomous navigation - the kind of work where your algorithms actually get deployed in the real world, on real hardware. 

We're looking for someone who can drive computer vision forward on our platform, not just contribute to it. 

No fluff, no bureaucracy theater. Just hard problems and people serious about solving them.

What you'll work on

• Lead the design, development, and optimization of CV algorithms for localization, mapping, and navigation - this is your area to own.
• Develop and implement algorithms for things like object detection, segmentation, SLAM, 3D scene reconstruction, visual odometry, and sensor fusion (cameras, LiDAR, IMUs).
• Integrate CV modules with navigation and control systems so they actually hold up in the real world, not just in simulation.
• Work closely with software, hardware, and product teams to define requirements and ship robust, scalable navigation solutions.
• Stay on top of deep learning and robotics research - and bring the relevant pieces into the product.
• Design experiments, analyze results, iterate. Repeat until it works well.
• Write clear technical documentation and share progress with both internal teams and external stakeholders.

What we're looking for

• 5+ years working in computer vision, ideally in navigation, robotics, or autonomous systems.
• A track record of building and shipping real-time vision algorithms - detection, segmentation, tracking, or navigation, not just research prototypes.
• Hands-on experience deploying and optimizing models for edge devices.
• Master's or PhD in Computer Science, Robotics, Electrical Engineering, or something closely related.
• Strong Python and/or C++ skills.
• Comfortable with PyTorch or TensorFlow, and familiar with OpenCV for classical CV work.
• You can break down hard problems, communicate your thinking clearly, and don't need much hand-holding.

Nice to have

• Knowledge of SLAM and related models.
• Familiarity with MAVLink, ArduPilot, or PX4.
• Publications or open-source contributions in vision or robotics — always a good sign.

Experience in fraud detection (highly preferred) + ability to independently scope and lead ML project end-to-end

Requirements

Position name: Senior Data Scientist — Anti-Fraud System

Level: Senior / Middle+

Hard skills requirements (including years):

• Strong experience in Data Science / Machine Learning
• Experience in fraud detection systems — highly preferred
• Ability to transition rule-based systems to ML/predictive models
• Experience with near real-time data processing
• Strong knowledge of statistical modeling and ML algorithms
• Python (preferred stack, final decision left to the DS)
• SQL and database proficiency
• Ability to independently scope a data environment and define technical approach

Soft skills requirements:

• Ability to independently lead a project end-to-end
• Strong communication skills (stakeholder alignment required)
• Self-driven, proactive, consultative mindset

Office/Remote: Remote

Project tasks:

• Scope existing rule-based fraud detection system (16 static flag types) and define technical approach
• Propose and implement ML stack and architecture
• Evolve system into dynamic, predictive, learning-based fraud detection model
• Work toward near real-time fraud processing as the project scales
• Work as part of 2-person AI team with full ownership of the anti-fraud project
• Facilitate stakeholder alignment

English level: Upper-Intermediate

Meet the YozmaTech

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster.

We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact.
Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

Our client is looking for a Data Science / AI Engineer to help build an autonomous platform that turns product requirements into production-grade code.

The product leverages AI to automate development workflows and dramatically increase R&D productivity. Already in production with active customers, the team is now scaling both the technology and impact.

Key Requirements:
🔹 7+ Years Experience: Deep professional background in AI/Data Science;
🔹 Agent Expert: Proven experience building high-quality agentic systems—specifically dealing with planning, tool-calling, and self-correction loops;
🔹 Sophisticated Retrieval: Expertise in building retrieval systems that can deal with real, complex cases (not just basic vector search);
🔹 Technical Excellence: Expert-level Python. You must be able to contribute to a production-grade backend and bridge the gap between a model's output and a functional tool;
🔹 AI Native: Power user of Claude and Cursor;
🔹 Advantage: Hands-on experience with LLM Evaluation suites and moving agentic systems from "cool demo" to "production reliable.";
🔹 Production Focus: Experience delivering solutions that are robust, reliable, and maintainable in real-world, customer-facing environments;
🔹 Database Skills: Experience with indexing, vector databases, and data retrieval at scale;

What you will do:
🔹 Planning & Reasoning: Design and optimize multi-step planning systems that allow agents to decompose high-level requirements into executable, low-error technical strategies;
🔹 Agentic Retrieval: Architect retrieval systems (GraphRAG, hybrid search) that can handle real-world codebase complexity, ensuring agents retrieve the right context for the right task;
🔹 Evaluation & Evals: Build robust, automated evaluation frameworks to measure agent success and reliability. You'll define what "high-quality execution" looks like in a machine-readable way;
🔹 Performance Optimization: Use few-shot learning, prompt engineering, and targeted fine-tuning to make agentic workflows deterministic and reliable in production;
🔹 From Demo to Production: Move beyond "agent-in-a-box" prototypes. You are responsible for the stability and quality of agents performing end-to-end SDLC tasks;
🔹 Customer Impact: Work closely with product and engineering teams to understand customer needs, solve real-world problems, and deliver solutions that move the needle for customers;
🔹 End-to-End Ownership: Take responsibility for projects from research and prototyping through to production deployment and ongoing optimization;
🔹 Product Mindset: Bring a product-oriented approach, proposing improvements and new features that align with business goals and customer requirements;
🔹 Collaboration: Communicate effectively with cross-functional teams and, when needed, with customers to gather feedback and ensure solutions meet real-world needs;
🔹 Proactive Problem Solving: Identify and address bottlenecks or new opportunities in agentic workflows and retrieval systems;

Interview stages:
🔹 HR Interview;
🔹 Technical Discussion ;
🔹 Practical Session ;
🔹 Team Fit Conversation ;
🔹 Final Review;
🔹 Reference Check;
🔹 Offer;

Why Join Us?

At YozmaTech, we’re self-starters who grow together. Every day, we tackle real challenges for real products – and have fun doing it. We work globally, think entrepreneurially, and support each other like family. We invest in your growth and care about your voice. With us, you’ll always know what you’re working on and why it matters.
From day one, you’ll get:
🔹 Direct access to clients and meaningful products;
🔹 Flexibility to work remotely or from our offices;
🔹 A-team colleagues and a zero-bureaucracy culture;
🔹 Opportunities to grow, lead, and make your mark.

After you apply

We’ll keep it respectful, clear, and personal from start to offer.
You’ll always know what project you’re joining – and how you can grow with us.

Everyone’s welcome

Diversity makes us better. We create a space where you can thrive as you are.

Ready to build something meaningful?

Let’s talk. Your next big adventure might just start here.