Jobs Data Science

We are looking for a Middle AI/ML Engineer to develop and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will focus on building and iterating on machine learning and LLM-based solutions, integrating them into Foundry workflows to support analytics, automation, and decision-making. You will collaborate closely with data engineers, business analysts, and domain experts to deliver practical, production-ready AI solutions.

Responsibilities:

• Develop and enhance machine learning and AI models to support predictive analytics, classification, forecasting, and AI-assisted workflows.
• Build AI and ML solutions within Palantir Foundry, using Python and existing Foundry pipelines, Ontology objects, and workflows.
• Apply LLMs and NLP techniques (e.g. prompt engineering, fine-tuning, embeddings, retrieval-augmented workflows) using Palantir AIP for enterprise use cases.
• Collaborate with data engineers to understand data sources, ensure data quality, and prepare datasets for model training and inference.
• Conduct experiments, evaluate model performance, and iterate on features and model approaches.
• Integrate AI models into Foundry workflows to surface insights and support business processes.
• Support model deployment and monitoring by following established team standards and best practices.
• Work closely with business and domain stakeholders to translate requirements into practical AI-driven solutions.
• Document model behavior, assumptions, and limitations to support transparency and compliance.
• Stay up to date with applied AI and GenAI trends and contribute ideas under guidance from senior team members

Requirements:

• 3+ years of experience in machine learning, AI engineering, or applied data science.
• Strong Python skills; experience with ML libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Practical experience with RAG architectures, vector databases, and retrieval strategies
• Hands-on experience with LLMs, NLP, or GenAI use cases (e.g. prompt design, embeddings, text classification, summarization).
• Practical understanding of the ML lifecycle: data preparation, feature engineering, model training, evaluation, and iteration.
• Experience working with structured data (tabular, time series); exposure to text or unstructured data is a plus.
• Familiarity with enterprise data environments and collaborative development workflows.
• Ability to clearly explain model results and AI behavior to non-technical stakeholders.
• Upper-Intermediate English or higher.

Nice to have: 

• Proficiency in Foundry Ontology, Object Builders, and Code Repositories.
• Experience in big pharma or highly regulated industries.
• Knowledge of data privacy, compliance, and security best practices in AI applications.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).

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 Senior AI/ML Engineer to design, develop, and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will take ownership of developing production-ready machine learning and LLM-based solutions, from understanding business needs and exploring data to designing technical approaches, implementing solutions, and integrating them into Foundry workflows. You will work closely with data engineers, business analysts, and domain experts, contribute to technical decisions, and help establish best practices for building scalable and reliable AI solutions.

Key Responsibilities:

• Design and develop AI/ML solutions for predictive analytics, classification, forecasting, automation, and AI-assisted workflows within Palantir Foundry, leveraging Python, Ontology objects, pipelines, and workflows.
• Design, implement, evaluate, and optimize LLM/NLP and RAG solutions using Palantir AIP, including prompt engineering, embeddings, retrieval strategies, vector search, and text processing.
• Own the end-to-end lifecycle of AI solutions, from experimentation and model development to deployment, monitoring, and continuous improvement.
• Collaborate with data engineers to understand data sources, ensure data quality, and design efficient and scalable data processing approaches.
• Integrate AI solutions into production workflows and optimize them for accuracy, reliability, latency, scalability, and cost-efficiency.
• Contribute to technical architecture and design decisions, including model, framework, and tool selection; proactively identify technical risks, improvement opportunities and proactively propose solutions.
• Work with business and domain stakeholders to translate business needs into practical, scalable, and production-ready AI solutions, clearly communicating technical decisions and model limitations.
• Identify technical risks, limitations, and opportunities for improvement and proactively propose solutions.

Requirements:

• 4+ years of experience in machine learning, AI engineering, applied data science, or related fields.
• Strong Python skills and hands-on experience with ML frameworks such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
• Strong practical experience with LLMs, NLP, or GenAI applications, including prompt engineering, embeddings, text processing, summarization, or similar use cases.
• Solid hands-on experience designing and implementing RAG architectures, vector databases, and retrieval strategies.
• Strong understanding of the ML lifecycle, including data preparation, feature engineering, model development, evaluation, deployment, and monitoring.
• Experience working with both structured and unstructured data, including tabular data, time series, text, and documents.
• Ability to independently analyze ambiguous problems, propose technical approaches, and drive solutions from concept to implementation.
• Strong communication skills, with the ability to explain AI concepts, technical decisions, and model behavior to non-technical stakeholders.
• Upper-Intermediate English or higher.

Nice to Have:

• Proficiency in Foundry Ontology, Object Builders, and Code Repositories.
• Experience in big pharma or highly regulated industries.
• Knowledge of data privacy, compliance, and security best practices in AI applications.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)

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

Team Summary

Our team is committed to providing high-quality data across a wide array of domains for our clients. We offer a comprehensive suite of services and solutions specifically designed to enhance data programs for AI products. Our expertise encompasses the entire data management lifecycle, from data requests and collection to processing and the delivery of ready-to-use datasets. We provide an extensive range of data services, including initial collection, annotation, and thorough analysis.

Job summary

We are looking for a highly skilled Data Annotator with extensive experience in data annotation, particularly within the Computer Vision domain. This role involves precise labeling and classification of data, ensuring data quality and consistency to support the advancement of machine learning and artificial intelligence initiatives.

Responsibilities and Duties

• Label videos or images according to given instructions
• Check and validate annotations to ensure compliance with standards
• Enhance annotation tools, methods, and instructions to increase efficiency and quality
• Collaborate with internal and customer teams to align on annotation requirements
• Monitor errors and evaluate annotation quality
• Research new tools and new types of annotation and communicate with internal and external teams regarding these findings
• Focus on increasing output speed to provide an efficient approach that balances velocity and quality

• Create documentation and guidelines for new types of tasks

   

Qualifications and Skills

• Hands-on experience using specialized platforms and tools for annotation
• Previous experience with several types of annotation.
• High attention to detail and ability to notice the slightest deviatations and inconsistencies in data labeling
• Quick learning of new data annotation tools
• Good analytical thinking 
• Basic Excel and SQL skills
• Good written and spoken English
• Exceptional self-management and autonomy in the workplace

Nice to have

• Experience automating annotation processes (scripts, API integration)

• Experience with Git, Jira and Confluence

   

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 compensation and perks. Annual performance review
• Opportunity to receive a Performance Bonus for your individual achievements and a Loyalty Bonus recognizing your dedication to the company
• Gig-contract
• 21 paid vacation days per year, paid public holidays according to Ukrainian legislation
• Development opportunities like corporate courses, knowledge hubs, and free English classes as well as educational leaves
• Medical insurance is provided from day one. Sick leaves and medical leaves are available
• Remote working mode is available within Ukraine only
• Free meals, fruits, and snacks when working in the office.

Build the core data engineering capability that enables WPP Open applications, AI agents, analytics products, and business workflows to securely discover, access, combine, govern, and activate data across enterprise systems, client environments, media platforms, and third-party providers.

We are seeking four senior engineering specialists who will be responsible for implementation and delivery of key platform capabilities. While architecture leadership is provided by the platform architecture team, these hires are expected to bring deep expertise, contribute to solution design, challenge assumptions, and guide implementation decisions based on industry experience.

Requirements

Implement the capabilities required to acquire, standardize, harmonize, and operationalize external marketing, media, commerce, and third-party datasets at scale. 

• Strong experience with SQL, Python, and cloud-based platforms like AWS, GCP, or Azure.
• Solid understanding of data modelling, pipelines and orchestration tools (Airflow, dbt, or similar).
• Familiarity with modern data ecosystems — e.g. Spark, Databricks, Snowflake, BigQuery or Redshift.
• Experience working with CI/CD, version control and testing best practices.
• A proactive approach to solving problems and improving systems.
• Excellent communication skills — you can translate technical concepts into language anyone can understand.
• A passion for data and how it can drive better decisions in media, marketing and beyond.

Experience with technologies and platforms such as

• Adverity, Fivetran, Airbyte
• Google Ads, DV360, Campaign Manager 360, Search Ads 360
• Meta, TikTok, Amazon Advertising, LinkedIn, Pinterest, Trade Desk
• Marketing, advertising, commerce, audience, or measurement data ecosystems

Job responsibilities

• Building and maintaining external data integrations
• Implementing reusable ingestion frameworks
• Standardizing and harmonizing media and marketing datasets
• Integrating third-party and client-owned data sources
• Supporting real-time and batch data acquisition patterns
• Providing expert input into data acquisition and onboarding approaches

About Digis
Digis is a European IT company with 250+ specialists delivering complex products for 70+ clients across the U.S., Europe, and Canada. We operate in a remote-first environment and focus on long-term collaboration, stable projects, and transparent processes.

About the Project
An AI-driven real-time market intelligence platform for the global fresh produce industry. The platform helps growers, retailers, distributors, and investors make faster, data-driven decisions.

Requirements

• 5+ years of professional experience in Data Science.
• Strong Python skills and experience with ML libraries.
• Strong SQL skills and hands-on experience with BigQuery.
• Strong experience with GCP.
• Experience with advanced machine learning frameworks and libraries such as XGBoost, LightGBM, PyTorch, or TensorFlow.
• Upper-Intermediate+ English level

Responsibilities

• Analyze complex multivariable datasets and identify key patterns and drivers.
• Build forecasting and classification models using statistical, ML, and deep learning approaches.
• Engineer features based on seasonality, weather, trade flows, and regional dynamics.
• Design and maintain model evaluation and backtesting frameworks.
• Assess model uncertainty, explainability, and performance.
• Monitor model drift and continuously improve model quality.
• Prototype LLM and AI-agent use cases.
• Collaborate with engineering teams to deploy models into production.

Advantages

• High ownership of the scientific and modeling layer.
• Work with unique global weather, market, trade, and supply-chain datasets.
• Build models that directly impact customer-facing products.
• Direct collaboration with CTO, founders, and senior leadership.
• Freedom to experiment with new approaches and technologies.
• Remote-first working environment.

We Offer

• 20 paid vacation days per year
• 5 paid sick days
• Compensation for professional courses
• English learning support
• Work equipment
• Transparent communication and processes
• Opportunity to switch projects within Digis
• Corporate psychologist

ORIL is looking for a Data Integration Specialist to lead and manage the data integration architecture of our AI-driven facilities management platform. The ideal candidate will possess strong expertise in optimizing data pipelines, resolving intricate integration issues, and ensuring uncompromising data quality.

About the Project

A platform shaping the future of facilities management by connecting buildings, occupants, service providers, and operatives. It streamlines soft FM services so property managers and service providers can plan, source, and manage their portfolios more efficiently and at lower cost, delivering real-time transparency across every site. The ecosystem spans FM service workflows, IoT-connected building sensors, third-party FM platforms, mobile and web clients, and event-driven microservices.
 

What You'll Do

• Design, build, and maintain scalable data pipelines and integrations across internal microservices, third-party FM platforms, IoT sensors, and external APIs.
• Design and implement ETL/ELT pipelines on Azure Databricks, building on Delta Lake and Lakehouse architecture to ingest, model, transform, and serve structured and semi-structured data.
• Define and own the data modelling layer - schemas and domain models that keep data structured and validated before ingestion, avoiding raw data sprawl.
• Work with event-driven architectures (message queues, pub/sub, event streams) to enable real-time data propagation and workflow automation.
• Define and enforce data mapping, transformation rules, and validation standards across all data flows.
• Collaborate with backend engineers, product managers, and data stakeholders to translate integration requirements into robust solutions.
• Monitor integration health, set up alerting, and diagnose pipeline failures to maintain high availability and data fidelity.
• Document integration patterns, data contracts, and API specifications for the wider engineering team.
• Contribute to platform-wide data quality, observability, and reliability standards.

What We're Looking For

• 4+ years of professional experience in a data integration, data engineering, or backend integration role.
• Hands-on experience with Azure Databricks for data engineering, pipeline orchestration, and large-scale transformations.
• Strong proficiency in Python for data engineering, pipeline development, and transformation logic.
• Strong understanding of data modelling, schema design, and data transformation patterns.
• Experience with relational and/or NoSQL databases (PostgreSQL, Cosmos DB, or similar).
• Understanding of distributed systems, microservices architectures, and cloud-native environments.
• High attention to detail and a strong sense of ownership over data quality and integration reliability.
• Comfort working across engineering, product, and business teams.
• English: Upper-Intermediate+

Nice to Have

• Experience with Azure Service Bus or similar event-driven messaging platforms (pub/sub, message queues, async workflows).
• Exposure to real-time streaming data and sensor telemetry workflows.
• Knowledge of data governance, lineage tracking, or observability tooling.

We offer:

• Competitive compensation;
• Accounting support services;
• Flexibility to work from anywhere (fully remotely or in our office in Lviv);
• Comprehensive day-off policy, including public holidays and special events;
• Education & certification budget + corporate education events;
• Wellness budget;
• An agile environment and culture that promotes personal and team development.

Sii Ukraine is a subsidiary of Sii Poland — the leader in IT, engineering, and consultancy services with over 7500 IT experts in Poland and more than 250 prestigious customers. We are looking for ambitious and top-quality professionals to join our project teams.

We are looking for a Senior Big Data Developer to join a project focused on building data-driven solutions and integrations using the Databricks platform.

You will work on backend logic, API integrations and application components within Databricks Apps, contributing to scalable and maintainable solutions that integrate with enterprise systems and procurement processes.

Responsibilities:

• Develop and maintain applications and data solutions using Databricks
• Build and configure Databricks Apps, Workflows, Delta Lake and Unity Catalog
• Develop backend logic using Python, including routing, validation and business logic
• Design and implement integrations with external systems through REST APIs
• Work with JSON, OAuth 2.0 and API-based content routing
• Develop application interfaces using Streamlit or React within Databricks Apps
• Implement and maintain data and API integration flows
• Write unit and integration tests to ensure solution quality and reliability
• Use Git and CI/CD practices for development and deployment
• Implement logging, monitoring and troubleshooting mechanisms
• Collaborate with other developers, architects and business stakeholders

• Contribute to technical decisions and continuous improvement of the solution

   

Requirements:

• Strong commercial experience as a Big Data / Data / Software Developer
• Hands-on experience with Databricks
• Practical knowledge of:
  • Databricks Apps
  • Databricks Workflows
  • Delta Lake
  • Unity Catalog
• Strong Python skills, particularly for backend development
• Experience with REST APIs, JSON and OAuth 2.0
• Understanding of API-based content routing
• Experience with Streamlit or React
• Good understanding of software engineering practices
• Experience with Git and CI/CD
• Experience writing unit and integration tests
• Experience with logging, monitoring and troubleshooting
• Ability to work independently and communicate effectively with technical and business stakeholders
• English at a level sufficient for working in an international environment
• Tax residence in Ukraine required

Nice to Have:

• Experience with E-Invoicing solutions
• Knowledge of SAP Ariba
• Experience integrating with ERP or procurement systems
• Knowledge of UBL / PEPPOL
• Experience working with enterprise integration platforms

We are looking for a Game Mathematician to work on slot games within an iGaming product. This role is for someone who can turn mathematics into an engaging and well-balanced gaming experience, works confidently with probabilities, RTP, and simulations, and collaborates effectively with developers and QA.

Responsibilities
• Design and calculate mathematical models for slot games (RTP, volatility, hit rate, max win).
• Build and balance core game elements: paytables, reels / weights, wild & scatter logic, free spins, respins, multipliers, bonus features.
• Prepare complete mathematical documentation for implementation: formulas, rules, tables, edge cases, configurations.
• Run and analyze Monte Carlo simulations to validate RTP, payout distribution, and volatility.
• Prepare math validation reports.
• Support developers and QA during integration and testing phases.

Optional / Additional Responsibilities
• Research iGaming trends and competitor mechanics.
• Participate in the full game lifecycle (from concept to release).
• Analyze player behavior using mathematical and statistical data.

Requirements
• Commercial experience in slot math / casino game mathematics.
• Strong understanding of probability theory, combinatorics, and statistics.
• Clear understanding of RTP structure (base vs bonus contribution), volatility management, and feature triggers.
• Ability to produce clear and well-structured technical documentation for engineering teams.
• Strong analytical thinking, attention to detail, and ownership of results.

Nice to Have
• Confident knowledge of Python.
• Experience building simulation scripts / tools (config-driven, reproducible simulations, result export).
• Experience with jackpot / progressive models.
• Understanding of compliance and regulatory requirements in iGaming.

Skylum empowers millions of photographers to create incredible images. Our award-winning photo editing software combines AI-powered automation with full creative control. We make editing enjoyable, easy, and accessible for everyone.
You’ll join an environment where growth, learning, and creativity are encouraged. Flexible schedules, trust-based workflows, and a supportive team give you everything you need to focus on your best work.
🇺🇦 Proudly Ukrainian, Skylum stands with Ukraine through action, regularly supporting organizations that help accelerate our victory.

 

We’re looking for a Data Scientist to understand user behavior and develop machine learning models that improve user experience, product adoption, retention, and purchasing conversion.

You will join our Core Analytics team and collaborate with Data Engineers, Analytics Engineers, and Product and Marketing analysts. You will identify meaningful behavioral patterns, turn them into predictive features, and train models that support personalization and better product decisions.

Our data environment: 

Python, SQL, Apache Airflow, MySQL, ClickHouse, Parquet, AWS, and Tableau.

Why join us: 

You will help shape applied data science within Core Analytics and influence how our products respond to user needs. Your work will turn behavioral data into models and experiences that help users discover value, adopt relevant features, and make repeat purchases.

 

Required experience:
 

• Experience delivering data science or machine learning solutions with measurable product or business outcomes.
• Strong Python skills for data preparation, feature engineering, model training, and evaluation using pandas, NumPy, scikit-learn, and related libraries.
• Strong SQL skills for analyzing event-level data and building reliable modeling datasets.
• Practical experience with classification, regression, clustering, and gradient boosting methods such as XGBoost, LightGBM, or CatBoost.
• Experience identifying behavioral patterns and creating predictive features from user activity, event sequences, purchase history, and lifecycle data.
• Knowledge of the full model lifecycle: target definition, dataset preparation, hyperparameter tuning, validation, deployment, monitoring, and retraining.
• Strong understanding of statistics and experimentation, including data leakage, class imbalance, selection bias, temporal validation, and prediction calibration.
• Familiarity with deep learning concepts and a clear understanding of when neural networks offer value over simpler approaches.
• Experience with Git, reproducible workflows, and collaboration with engineers to productionize models.
• Ability to translate business goals into modeling problems and explain findings, limitations, and recommendations clearly.

Key Responsibilities: 
 

• Explore user journeys, habits, and behavioral patterns to identify signals associated with adoption, engagement, upgrades, repeat purchases, and churn.
• Define prediction targets and develop features, labels, and training datasets from product events, transactions, and customer data.
• Train, tune, and evaluate machine learning models for purchase propensity, customer lifetime value, churn risk, and next-best actions.
• Develop segmentation, recommendations, and personalization models; apply deep learning where the problem and available data justify it.
• Partner with engineers to deploy models and integrate predictions into product experiences and business workflows, including monitoring and retraining.
• Validate business impact through experiments, distinguishing predictive relationships from causal effects and balancing conversion with user satisfaction and long-term retention.

Nice to have:
 

• Hands-on experience with PyTorch or TensorFlow.
• Experience with recommendation systems, ranking, embeddings, or sequential models for user behavior.
• Knowledge of uplift modeling and causal inference to identify which interventions improve outcomes for different users.
• Experience with subscription, mobile, or marketplace products, including upgrade propensity and repeat-purchase prediction.
• Familiarity with Airflow, ClickHouse, AWS, experiment tracking, feature stores, and model monitoring.

What we offer
For personal growth:
 

• A chance to work with a strong team and a unique opportunity to make substantial contributions to our award-winning photo editing tools;
• An educational allowance to ensure that your skills stay sharp;
• English, German and Polish classes to strengthen your capabilities and widen your knowledge.

For comfort:
 

• A great environment where you’ll work with true professionals and amazing colleagues whom you’ll call friends quickly;
• The choice of working remotely or in our office space located on Podil, equipped with everything you might need for productive and comfortable work.

For health:
 

• Medical insurance;
• Twenty-one days of paid sick leave per year;

For leisure:
 

• Twenty-one days of paid vacation per year;
• Fun times at our frequent team-building activities.

What to expect when you apply
 

• An interview with our Talent Acquisition Manager
• Professional  interview
• Technical interview 
• Interview with CEO
• And finally, your job offer!

We are looking for a Computer Vision / C++ Engineer to join our team and work on real-world computer vision systems.

Responsibilities:
 

- Develop and maintain computer vision solutions in C++;

- Work with geometric computer vision (projective and epipolar geometry);

- Implement classical CV algorithms (demosaicing, tracking, optical flow, color calibration, image enhancement);

- Fine-tune existing deep learning models (e.g. YOLO) and train custom models using PyTorch;

- Deploy DL models in C++ using inference runtimes (ONNX Runtime, OpenCV DNN or similar);

- Implement model output decoding and post-processing;

- Develop camera-related software;

- Write efficient multi-threaded code.

Requirements:
 

- Strong C++ skills;

- Solid background in computer vision;

- Practical experience with deep learning for CV and PyTorch;

- Experience with deploying models to C++ applications and inference runtimes;

-Experience with multi-threaded programming and camera systems.

We are looking for a Senior Data Scientist

Responsibilities:

• Analyze large and complex data to discover hidden patterns and opportunities;
• Develop and own end-to-end highly scalable data pipelines;
• Develop state-of-the-art machine learning models, and algorithms and build solutions in monetization fields;
• Provisioning data models for real-time (online) processing;
• Shape new data products, and constantly improve the existing products;
• Collaborate with multiple teams including Product, BI, Analysts, DevOps, R&D and Marketing to lead and accomplish overall solutions;
• Oversee a complete release to production, including analyzing requirements, testing, monitoring and measuring results, multitasking, and quickly responding to critical issues.
  
  Requirements:
• B.Sc./M.A/M.Sc. degree in Computer Science, Engineering, Math, Statistics, or other equivalent fields;
• 6 years as a Data Scientist - a strong background in ML concepts and models;
• Hands-on experience with Python, especially with data science ML libraries (regression& classification algorithms e.g. XGB or LGBM, recommendation system algorithms, etc.;
• Understanding of databases and SQL for data retrieval;
• Monitoring and alerting tools (e.g. Grafana, Kibana).
   

Will be a plus:

• Knowledge in the programmatic advertising landscape – DSPs, SSPs, exchanges – significant advantage;
• Experience with relational (e.g. Vertica, VoltDB) and non-relational (e.g. MongoDB) databases;
• Experience with PMML.

Duration: long-term

We are looking for a Middle Data Scientist with strong hands-on experience in time-series, deep learning, and Python development.

This role is a good fit for someone with 3+ years of professional experience in Data Science or Machine Learning, a strong understanding of neural networks, and practical experience developing predictive models for time-series and tabular data.

We expect solid knowledge of different neural network architectures, including recurrent and convolutional networks, as well as practical experience designing, training, tuning, validating, and deploying models.

Strong Python programming skills are essential for this position. You should also be confident working with statistics, data analysis, and production-oriented Data Science code.

What you will work on:

• Perform exploratory data analysis and prepare statistical summaries for hypothesis testing and data-driven decision-making.
• Build data preparation and feature engineering pipelines used by predictive models.
• Design and implement predictive modelling approaches.
• Continuously analyse and improve models already running in production.
• Take an active role in Python development related to end-to-end ML model delivery and support internal ML-related libraries.
• Tune loss functions, evaluation metrics, sample weights, hyperparameters, and other model components to improve model quality.

• Prepare detailed model evaluation reports, summarise findings, and communicate practical insights to stakeholders.

   

What we expect from you:

• At least 3 years of professional experience working as a Data Scientist or Machine Learning Engineer.
• Practical experience building custom neural networks with PyTorch.
• Strong knowledge of neural network architectures applicable to time-series forecasting and predictive modelling of tabular data.
• Experience working with layers such as LSTM, GRU, Conv1D, Dense, Dropout, and BatchNormalization, as well as activation functions including ReLU, Sigmoid, Tanh, and Softmax.
• Hands-on experience working with time-series datasets, including data loading, cleaning, preparation, and feature engineering with pandas and NumPy.
• Experience with the Darts library would be a significant advantage.
• Experience selecting and developing models available in Darts, as well as creating custom neural network architectures.

• Excellent Python knowledge and confidence working with libraries such as Scikit-learn, Pandas, PyTorch, and SHAP.

   

Python proficiency is particularly important for this role. Our projects require Data Scientists who can independently write, structure, and maintain Data Science functionality and supporting libraries.

You should also have:

• An understanding of statistics and data analysis.
• Experience selecting and tuning loss functions such as MSE, MAE, Cross-Entropy Loss, as well as custom losses suitable for forecasting problems.
• Experience with hyperparameter optimisation tools such as Optuna or Hyperopt.
• Ability to implement and optimise PyTorch training loops, including data loaders and training/validation stages.
• Knowledge of cross-validation approaches designed specifically for time-series data.
• Understanding of regularisation techniques used to reduce overfitting.
• Strong knowledge of model evaluation metrics, including MSE, RMSE, MAE, MAPE, and R-squared.
• Familiarity with backtesting approaches used to validate model performance.
• Experience with model deployment, including model serialisation and deployment for real-time services.
• Experience preparing visualisations with matplotlib, seaborn, or Plotly.
• Confident use of Git for version control and team collaboration.
• Strong self-management and organisational skills.

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.

If you’re a talented Data Scientist looking to be part of a fast-growing, innovative R&D team, shape the future of decision-making in business, work on cuttingedge technologies and vast amounts of global real-time data, affect billions of mobile users, and become an industry leader - then let’s talk! Start.io is a mobile data platform that enables organizations to uncover insights and make datadriven decisions that enhance strategies and drive growth. We are seeking a Senior Data Scientist to join our Data Science & Engineering team.

Responsibilities:

• Analyze large and complex data to discover hidden patterns and opportunities;
• Develop and own end-to-end highly scalable data pipelines;
• Develop state-of-the-art machine learning models, and algorithms and build solutions in monetization fields;
• Provisioning data models for real-time (online) processing;
• Shape new data products, and constantly improve the existing products;
• Collaborate with multiple teams including Product, BI, Analysts, DevOps, R&D and Marketing to lead and accomplish overall solutions;
• Oversee a complete release to production, including analyzing requirements, testing, monitoring and measuring results, multitasking, and quickly responding to critical issues.

Requirements:

• B.Sc./M.A/M.Sc. degree in Computer Science, Engineering, Math, Statistics, or other equivalent fields;
• 6 years as a Data Scientist - a strong background in ML concepts and models;
• Hands-on experience with Python, especially with data science ML libraries (regression & classification algorithms e.g. XGB or LGBM, recommendation system algorithms, etc.;
• Understanding of databases and SQL for data retrieval;
• Monitoring and alerting tools (e.g. Grafana, Kibana).

Will be a plus:

• Knowledge in the programmatic advertising landscape – DSPs, SSPs, exchanges – significant advantage;
• Experience with relational (e.g. Vertica, VoltDB) and non-relational (e.g. MongoDB) databases;
• Experience with PMML.

What we offer:

• Help and support from our caring HR team;
• 20 days of vacation;
• The exchange of experience and work with talented colleagues;
• Last but not least - valuable compensation for your efforts.

Important: after confirming your application on this platform, you’ll receive an email with the next step: completing your application on our internal site, LaunchPod. So keep an eye on your inbox and don’t miss this step — without it, the process can’t move forward.

Why join us

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! :)

About the role

We are looking for a Senior Data Scientist to develop predictive models and quantitative analytics that power risk-based vulnerability prioritization within a large-scale enterprise security program. You will structure and analyze massive security telemetry datasets, build ML algorithms to eliminate scanning noise and false positives, and establish unified data dashboards to drive adoption of data-driven security governance. The role requires 5+ years of data science experience with direct commercial application to vulnerability management, operating with full autonomy.

What you will do

• Develop predictive models and quantitative analytics to prioritize vulnerabilities based on contextual risk and business impact;
• Structure and analyze massive outputs of security data from across the enterprise ecosystem to support the ASPM framework;
• Create machine learning algorithms or statistical models to automatically identify and filter out scanning noise and false positives;
• Establish a unified data delivery structure and dashboards to drive the adoption of data-driven security governance.

Must haves

• 4+ years of commercial data science experience, operating completely autonomously with no required supervision;
• Advanced proficiency in Python, R, and SQL;
• Experience with machine learning frameworks such as TensorFlow and PyTorch;
• Experience with data visualization tools;
• Commercial experience applying data science to vulnerability management;
• Upper-intermediate English level.

Nice to haves

• Familiarity with Cloud Security Posture Management (CSPM) data outputs (e.g., Wiz).

The benefits of joining us

• Professional growth: Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps
• Competitive compensation: We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities
• A selection of exciting projects: Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands
• Flextime: Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office – whatever makes you the happiest and most productive.

Meet Our Recruitment Process

Asynchronous stage – An automated, self-paced track that helps us move faster and give you quicker feedback:

• Short online form to confirm basic requirements
• 30–60 minute skills assessment via Codility – a platform founded in Poland that helps us provide quicker feedback and streamline this stage of the process.
• 5-minute introduction video

Synchronous stage – Live interviews

• Technical interview with our engineering team (scheduled at your convenience)
• Final interview with your future teammates

If it’s a match — you’ll get an offer!

Join Sigma Software to help build advanced machine learning solutions for one of the large-scale players in the programmatic advertising ecosystem. We are looking for a Senior Machine Learning Engineer with strong production ML expertise and deep interest in real-time optimization systems, large-scale behavioral data, and AdTech challenges.

In this role, you will work with a dedicated Sigma Software team on a predictive modeling platform integrated with a live ad exchange processing hundreds of millions of auction requests daily. You will contribute to sophisticated ML solutions involving bid optimization, calibration, counterfactual evaluation, and constrained decision-making systems.

We as a company offer the opportunity to work on technically challenging products, collaborate with experienced engineers and data scientists, and make a direct impact on large-scale production systems.

CUSTOMER

Our Customer is a technology company operating supply-side infrastructure within the programmatic advertising ecosystem. The company manages a high-scale ad exchange platform and is investing in predictive decisioning capabilities to improve advertising performance, audience targeting, and campaign optimization through advanced machine learning technologies.

PROJECT

The project focuses on building a predictive modeling and optimization platform on top of a live ad exchange environment. The platform evaluates and filters advertising supply in real time, predicts high-performing audience contexts, builds look-alike audiences from small seed datasets, and optimizes campaign performance across multiple business objectives and operational constraints.

The team works on complex machine learning challenges including censored bid-landscape modeling, sparse and delayed conversion attribution, calibration systems, counterfactual evaluation, and constrained optimization models. The solution is designed for large-scale production use and close collaboration with the Customer’s internal data science organization.

Job Description

• Build and improve censored bid-landscape models to estimate clearing-price distributions from partially observed auction data
•  Develop real-time win probability estimation models responsive to bid pricing dynamics
• Design and implement hierarchical lift estimation models with confidence-bound-based selection strategies
• Build conversion propensity models using sparse, delayed, and aggregate-only labels
• Develop look-alike audience modeling approaches using positive-unlabeled learning and embedding-based nearest-neighbor techniques
• Implement advertiser-level calibration strategies while independently monitoring ranking and calibration quality
• Design robust offline evaluation frameworks using inverse-propensity scoring, doubly-robust estimators, and importance reweighting
• Define exploration strategies and propensity logging approaches to ensure reliable downstream correction and evaluation
• Develop constrained optimization mechanisms for campaign objectives, pricing constraints, and volume targeting
• Contribute to data diagnostics, capability assessments, and evidence-based model recommendations
• Collaborate with the Customer team during post-launch tuning and performance validation cycles
• Prepare technical documentation and knowledge transfer materials for the Customer’s internal data science team
• Participate in architecture discussions and contribute to scalable ML platform design decisions

Qualifications

• 5+ years of experience in Machine Learning or Data Science with production-grade models measured against business KPIs
• Strong Python skills including numpy, pandas, and scikit-learn
• Strong SQL skills and experience working with large-scale datasets
• Deep practical experience with XGBoost, LightGBM, or CatBoost
• Strong understanding of regularization, calibration methods, and categorical feature handling
• Strong knowledge of probability, statistics, confidence intervals, and statistical power analysis
• Experience with feature engineering for structured and behavioral datasets
• Hands-on experience with Spark or PySpark
• Practical knowledge of experimentation frameworks and A/B testing methodologies
• Experience with advanced validation approaches including temporal splits, leakage detection, drift analysis, and slice-based metrics
• Understanding of explainability techniques such as SHAP and permutation importance
• Upper-Intermediate English level or higher

WILL BE A PLUS

• Experience in AdTech modeling including CTR/CVR prediction, bid-landscape modeling, audience segmentation, and RTB mechanics
• Experience working with sparse, delayed, or censored labels
• Knowledge of attribution modeling, survival analysis, and positive-unlabeled learning
• Practical experience with counterfactual and off-policy evaluation techniques
• Understanding of calibration methods including isotonic regression and Platt scaling
• Experience with hierarchical, empirical-Bayes, or partial-pooling models
• Knowledge of constrained or multi-objective optimization approaches
• Experience with uplift modeling and causal inference methods
• Experience with Vertex AI or similar managed ML training environments
• Publications, competitive modeling achievements, or open-source contributions related to Machine Learning or AdTech

PERSONAL PROFILE

• Strong analytical and problem-solving skills
• Ability to work effectively in a highly data-driven environment
• Strong communication and stakeholder management abilities
• Ability to explain complex modeling decisions to technical and non-technical audiences
• Proactive mindset with strong ownership mentality
• Attention to detail and scientific rigor in experimentation and evaluation