Jobs Data Scientist

ZentixSoft is looking for a Senior Data Scientist! 🚀

Format: Full-Time Outstaffing, long-term engagement.

Location: Poland-based (Remote with readiness for occasional client meetings in Warsaw).
 

🏛️ Our Approach & Culture at ZentixSoft:

At ZentixSoft, we operate on trust and high autonomy. We have no micromanagement, no invasive time-trackers, and no minute-by-minute monitoring—we value a mature engineering mindset and freedom in decision-making.

However, freedom always equals personal responsibility. We measure work by concrete business outcomes, not logged hours. We expect you to take complete ownership of your domain, understand how your models impact commercial decisions, meet deadlines, and deliver production-grade results.

In this role, you will lead end-to-end data science for a SaaS platform in AgriTech / Supply Chain, working directly with the CTO, product team, and GCP engineers to build price, demand, and yield forecasting models.

🧩 Responsibilities:

• End-to-End Ownership: Own modeling from problem definition to production deployment, analyzing multivariate time-dependent data for forecasting and classification.
• Feature Engineering: Build complex features around seasonality, lead-lag effects, weather impact, and regional supply chain dynamics.
• Model Benchmarking & Validation: Design and evaluate XGBoost, LightGBM, ARIMA, and deep learning sequence models using temporal cross-validation, uncertainty estimation, and explainability frameworks.
• Production Deployment: Productionize batch and API models on GCP alongside data engineers, implementing drift monitoring and retraining pipelines.
• Modern AI Integration: Prototype LLMs and AI agents where relevant for automated insights.
• Business Impact: Present quantitative findings, trade-offs, and metrics clearly to business stakeholders and non-technical decision-makers.
   

🎓 Our Perfect Match (Requirements):

• Commercial DS Experience: 5+ years in Data Science, applied ML, or quantitative analytics.
• Core ML & Data Stack: Advanced Python (Pandas, NumPy), ML frameworks (XGBoost / LightGBM / PyTorch / TensorFlow), and SQL.
• Cloud & Data Warehouse: Hands-on experience with Google Cloud Platform (GCP) and BigQuery is a MUST.
• Time-Series Expertise: Proven track record in time-series forecasting with concrete quality metrics (e.g., MAPE, RMSE, WAPE) in real-world environments.
• Location & Mobility: Candidate MUST be based in Poland and willing to visit Warsaw occasionally for client meetings.
• Communication: Fluency in English with the ability to explain complex quantitative models in business terms.
   

➕ Nice to Have:

• Experience with weather, geospatial, commodity, or supply-chain data.
• Bayesian methods, probabilistic forecasting, causal inference, or optimization.
• Production experience with LLMs or AI agents.
• GCP Data Scientist / ML Engineer certifications.
   

📍 Project Details:

⏳ Format: Full-Time, long-term outstaffing.

📍 Location: Remote in Poland (with occasional trips to Warsaw).

About the Client

The Client has been servicing technology solutions to the New York City real estate industry for over a quarter of a century.  As there is no widely accepted MLS in the Manhattan real estate industry, the Client’s application environment is the system that transmits up to the minute inventory from one firm to another.  This system has grown from 10 firms and 300 listings exchanged daily to close to 500 firms and approximately 10,000 listings exchanged daily in accordance with REBNY's RLS guidelines.

The Client supports a full service listings system application which is in use by approximately 300 firms.  Their products include but are not limited to the full service listing application supporting both the agent end user and data entry, a mobile listings application, a variety of listing feeds, off the shelf and customized VOW options, and marketing services which consist of custom brochures, an interface with the New York Times' Ad times 2000 and a proprietary advertising tool known as Premium Marketing Opportunity (PMO).  The Client has a long standing history of successful data conversions, integrations, and development of customized business solutions.

Project details

The project is the sophisticated Listing Management System web application that allows New-York real estate agents find the right properties available for sale and rent, generates various reports for the agents' clients.

Your Team

We've created the team of 30+ team-members in Ukrainie and not going to stop. Due to new business challenges, we are ready to hire 1 more team member.

For now, our friendly team consists of FullStack .Net developers, Front end developers, QAs, DBAs, Researchers, BA and Designer.

What's in it for you

• Interview process that respects people and their time
• Professional and open IT community
• Internal meet-ups and resources for knowledge sharing
• Time for recovery and relaxation
• Bright online and offline events
• Opportunity to become part of our internal volunteer community

Responsibilities

The right candidate will collaborate and report directly to customers' market analyst who is located in New York. 

His/ her daily routine will consist in identifying and entering the information about new real estate objects available in New York into the customer's software system. 

Training will be provided.

Skills

• Upper-intermediate (or higher) English to collaborate with US market analyst on the daily basis.
• High typing speed to enter information about new objects on New York real estate market into the customer's software (training will be provided).
• Technical background (experience working with Excel/data) or a technical education
• Analytical skills to be able to distinguish existing real estate objects against new one (training will be provided).
• Working hours should be close to New York working hours as possible. At least from 13-00 till 21-00 UA time. But ability to shift it even more to 22-00 and late will be a HUGE plus.
• Responsible attitude towards entering correct information into the customer's software.
• Desire to learn New York real estate domain.
• Knowledge or previous experience in real estate domain is not required but will be a HUGE plus.

We are looking for a Data Scientist to join our client — an international technology company in the AdTech industry, headquartered in New York with offices around the world. The company develops software for digital advertising analytics and verification: its platform evaluates the quality of every ad impression — preventing ad fraud, ensuring brand safety and suitability, and verifying viewability and geo-targeting. Its clients include some of the world's largest brands, such as Vodafone and Mondelez. The Data Scientist will take ownership of improving existing models, building statistically robust solutions, and translating business challenges into mathematical problems that are integrated into the platform.
 

Responsibilities:

• Enhance, fine-tune, and continuously improve existing modeling solutions, including customizing open-source libraries to meet project requirements;
• Perform exploratory data analysis and feature engineering to build statistically robust, interpretable models that reflect domain knowledge;
• Keep up with emerging methods and best practices in causal inference and experimental design;
• Translate complex business challenges into well-defined mathematical problems and communicate findings as clear insights and actionable recommendations to external stakeholders;
• Participate in code reviews and provide feedback on model architecture, system design, and technical implementation;
• Collaborate with product and engineering teams to integrate data science solutions into the company's platform.
   

Requirements:

• 5+ years of relevant industry experience with a BA or BSc in science or engineering, or 2+ years of professional experience with an MSc or PhD in a related field;
• Solid understanding of regression techniques, statistical hypothesis testing, and experimental design;
• Strong hands-on experience with the scientific Python ecosystem: NumPy, Pandas, Statsmodels, Matplotlib, and similar libraries;
• Strong communication skills and the ability to explain complex concepts clearly;
• A proactive, curious, and self-motivated approach with a genuine interest in continuous learning;
• Availability for occasional evening meetings (7–9 PM Kyiv time);
• Fluent English (C1).
   

Nice to have:

• Experience writing SQL queries for data extraction, transformation, and analysis;
• Practical knowledge of Bayesian methods and their application to predictive modeling;
• Experience with AWS;
• Hands-on experience with probabilistic programming frameworks such as STAN, PyMC, or NumPyro;
• Understanding of marketing analytics: campaign allocation, performance measurement, and marketing budget optimization.
   

What we offer:

• Paid vacation.
• Paid sick leave.
• Courses and learning opportunities.
• Flexible schedule and fully remote work from any location.
  
  Send your CV!

Dataforest seeks a Tech/Team Lead Data Science to join a friendly, supportive team. We are Data Engineering company working on AI adoption in different industries.

We are looking for a person who likes challenges. This position offers the possibility of working as a Manager, however, to keep track of ongoing changes in the AI field and participate in AI projects.

As a Tech/Team Lead, you will collaborate with the CEO and CTO to define proper development processes, run an R&D practice, participate in pre-sale, and lead ongoing AI projects.

 You'll be a great fit if you have:

• 5+ years of experience in Data Science field;

• 4+ years of experience with Python;

• Strong management and leadership skills, leading the data scientists team;

• Knowledge of data algorithms and data structures is a MUST;

• Experience with business analysis and project management;

• Knowledge of DS and Machine learning algorithms.

• Experience with LLM, RAG , Langchain;

• Experience with Databricks, Snowflake (Optional);

• Knowledge of cloud solutions: AWS or Azure or GCP (Optional);

• Experience in multithreading/multiprocessing approaches;

• Proficiency with Docker, Kubernetes, and CI/CD pipelines;

• Previous experience in a Team Lead role;

 What you’ll do:

• Manage the data science department (10 people);

• Perform code reviews and data scientist assessments;

• Develop DS Architecture;

• Participate in pre-sales activities;

• Lead a data science projects;

• Write clean and well-structured code that is easy to read and maintain;

• Participate in decision-making processes related to design architecture, solution development, architectural, and code reviews;

• Develop high-load solutions;

• Conduct R&D work with new technology;

• Maintain high-quality coding standards within the team.

We ensure your growth with:

• Great networking opportunities with international clients and challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary fixed in USD;

• Paid vacation and sick leave;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team-building activities and corporate events.

About RiskSeal

RiskSeal is a B2B startup serving fintech clients globally. Our API-first credit risk management platform enables digital banks and consumer lenders to simplify onboarding through data-driven insights.

We are growing rapidly and value collaboration with passionate, creative professionals. Join us to innovate, contribute your expertise, and grow alongside our team.

Headquarters: Dallas, Texas, USA

European Office: Warsaw, Poland

Learn more: https://riskseal.io/ 

Job Description

We are looking for a motivated Data Scientist to join our team in a fully remote role. The ideal candidate has experience in credit risk modelling, strong Python and SQL skills, as well as hands-on experience with scoring models. You will build and optimize advanced credit risk and anti-fraud models by leveraging machine learning, anomaly detection, and alternative data alongside traditional scoring. Working with client data, you will translate complex algorithmic outputs into clear, actionable insights for clients, partners, and internal teams.

What we're looking for:

• 2+ years of hands-on experience in credit risk and credit risk modelling (must-have)
• Solid knowledge of classical methods (logistic regression, decision trees, scorecards) and ML (boosting, random forests, neural networks)
• Strong Python and SQL skills
• Background in a bank, fintech, or data vendor environment
• Experience with PD modelling, scoring, and portfolio performance metrics
• Practical understanding of credit risk strategy and portfolio management, including approval strategies, credit limits, and cutoff optimization
• Comfortable working end-to-end: from raw data to a validated, production-ready output
• Able to present findings clearly to non-technical audiences, including clients and business partners
• Upper-Intermediate English level or higher.

What you'll be doing:

• Build, validate, and improve credit risk and scoring models
• Work with our clients’ data to generate insights and deliver analysis that helps them make better decisions
• Present findings and new ideas directly to clients and partners
• Think about new analytical products and data solutions that RiskSeal can offer
• Collaborate with business, product, and tech teams to turn data insights into real value

Nice to Have

• Experience working with alternative data sources.
• Knowledge of model governance and validation frameworks.
• Experience presenting analytical solutions directly to clients.
• Exposure to fintech products, digital lending, or embedded finance.

What We Offer

● A fully remote, full-time role in a growing product fintech company
● A fast-paced environment with minimal bureaucracy and quick decision-making
● The opportunity to work on credit risk models, scoring solutions, and real client data
● Direct collaboration with business, product, and tech teams
● The chance to contribute to analytical products that create real value for clients
● Competitive compensation and opportunities for professional growth

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

About the Company

We are a European IT company with 200+ specialists delivering SaaS platforms, enterprise solutions, and cloud-native products for clients worldwide. We focus on building strong, long-term teams and supporting continuous professional growth.

About the Internship & Project

We are looking for a Trainee Data Scientist to join a project delivered for a UK-based marketing data platform. The client’s platform connects various marketing channels under one roof, helping businesses understand customer retention and acquisition through advanced Single Customer View dashboards and personalization tools. You will contribute to real client projects, focusing on Marketing Mix Modelling (MMM) and causal marketing measurement. We are looking for someone with strong statistical reasoning who is motivated to build real-world data science skills, work with e-commerce datasets, and grow into a specialized role.

Responsibilities

• Prepare, clean, and process real e-commerce and marketing datasets
• Build, validate, and diagnose Marketing Mix Models (MMM) using Python
• Analyze seasonality, promotions, and pricing, as well as model adstock/carryover and saturation
• Calculate incremental revenue and ROAS, build response curves, and develop budget optimization models
• Work closely with the Head of Data Analysis and CTO, actively questioning model outputs to ensure statistical accuracy
• Compare MMM results with experiments and other attribution methods, visualizing findings and eventually explaining technical results in simple client-facing language

Requirements

• Good foundation in Python for data analysis (pandas, NumPy, SciPy, scikit-learn)
• Solid knowledge of statistics and regression
• Understanding of model validation and the clear distinction between correlation and causation
• Up to 3 links to pet projects or an academic project demonstrating your best Data Science skills
• English level: Upper-Intermediate

Why This Internship is Exciting

• Great opportunity to enter a specialized and rapidly growing field of Marketing Mix Modelling (MMM)
• Work with real e-commerce datasets and influence real commercial decisions
• Receive strong mentorship from experienced professionals ready to teach you MMM, e-commerce marketing, and attribution
• Gain exposure to advanced tools like Bayesian MMM, PyMC, Google Meridian, and Meta Robyn
• A clear path from an internship to a Junior role, with the potential to become the company’s internal MMM expert and transition into client-facing responsibilities

We are the creators of a new fintech era!

Our mission is to change this world by making blockchain accessible to everyone in everyday life. WhiteBIT is a global team of over 1,200 professionals united by one mission — to shape the new world order in the Web3 era. Each of our employees is fully engaged in this transformative journey.

We work on our blockchain platform, providing maximum transparency and security for more than 8 million users worldwide. Our breakthrough solutions, incredible speed of adaptation to market challenges, and technological superiority are the strengths that take us beyond ordinary companies. Our official partners include the National Football Team of Ukraine, FC Barcelona, Lifecell, FACEIT and VISA.

Requirements:

We're looking for a DevOps engineer with 4+ years of hands-on experience, at least 2 of them spent building and running data or analytics infrastructure. You've designed systems that move, store, and serve data at scale. Warehouse maintenance is part of your daily routine, and writing Python, Bash, or SQL scripts is second nature. You treat data security as a core responsibility: you protect confidentiality, enforce zero-trust, least-privilege access, and automate everything you touch. Solid IaC skills are a must.

• IaC & CI/CD: Production experience with Terraform, Ansible, and Helm, plus CI/CD systems (GitLab CI, GitHub Actions, Jenkins, or ArgoCD). We expect you to design pipelines, not just use them.
• Containerization: Working knowledge of Docker and Kubernetes, including running data workloads on it (like Spark on Kubernetes, stateful services, operators).
• Cloud: Solid experience with AWS (S3, EC2, EMR, Redshift, Glue, IAM) or an equivalent cloud provider.
• Linux & Networking: Solid Linux administration skills and foundational networking knowledge relevant to distributed systems.
• Analytical Databases: Hands-on operation of ClickHouse and/or the Hadoop ecosystem (HDFS, Hive, YARN), including cluster setup, tuning, and scaling.
• Data Warehouses: Practical experience with Snowflake or Redshift, covering warehouse sizing, workload management, performance tuning, and cost control.
• Large Databases: Experience administering databases at terabyte scale: replication, backup and restore strategies, partitioning, and migrations with minimal downtime.
• SQL & Scripting: Strong SQL skills, including reading execution plans and optimizing heavy queries. Confident in Python and Bash for automation, data parsing, and investigation.
• Data Lakes & Object Storage: Working knowledge of S3-compatible storage, columnar formats, partitioning strategies, and data lifecycle management.
• Orchestration & Streaming: Familiarity with Airflow (or similar orchestrators) and Kafka, and how they fit into data pipelines.

Extra Credit / Big Pluses

• Experience with Tableau, Power BI, Looker, Superset, or similar BI tools, including administration, performance tuning, and data source design.
• Hands-on experience with dbt and analytics engineering practices.
• Experience with open table formats (Apache Iceberg, Delta Lake, Hudi) and query engines like Trino/Presto or Athena.
• FinOps experience in data platforms: managing Snowflake credits, Redshift clusters, and storage costs at scale.
• Spark performance tuning and job optimization.
• Change data capture (CDC) with Debezium or similar tools.
• Data quality tooling (Great Expectations, Soda) integrated into CI/CD.
• Golang or Rust tooling experience.
• Knowledge of data governance and compliance (GDPR, data retention, PII handling).
• Understanding of business processes in the FinTech/Banking/Crypto sector.

Responsibilities:

• Infrastructure Ownership: Own the infrastructure behind our data and analytics platform, from provisioning to daily operations. Keep it reliable, scalable, and cost-efficient as data volumes grow.
• Infrastructure as Code: Provision and configure all data infrastructure with Terraform, Ansible, and Helm. 
• CI/CD Pipelines: Build and maintain delivery pipelines for both infrastructure and data code (ETL jobs, Airflow DAGs, dbt models, schema migrations), with automated testing, safe rollouts, and fast rollback.
• Database & Warehouse Operations: Maintain ClickHouse, Snowflake, Redshift, and вPostgreSQL at multi-terabyte scale, handling replication, backups, upgrades, capacity planning, and disaster recovery.
• Data Lake Storage: Manage S3-compatible data lake storage, including partitioning, file formats, and lifecycle policies.
• Automation & Script Optimization: Refactor and automate Python, Bash, and SQL scripts to cut runtimes and eliminate manual work.
• Performance & Cost: Right-size clusters and warehouses, tune heavy queries, and keep compute and storage spend under control.
• Monitoring & Alerting: Cover data infrastructure with metrics, logs, and alerts for cluster health, pipeline SLAs, and job failures.
• Security & Access Control: Enforce least-privilege access, secrets management, encryption, and auditability for sensitive data.
• BI Infrastructure: Support the infrastructure behind Tableau or similar BI tools.
• Big Data Platforms: Deploy, tune, and troubleshoot Hadoop, Spark, and Kafka clusters in production.
• Collaboration: Work with data engineers, analysts, and developers to turn their workloads into solid infrastructure decisions.
• Security & Access Control: Implement role-based access, secrets management, encryption at rest and in transit, and auditability for sensitive datasets in line with regulatory requirements.

Working terms

Immerse yourself in Crypto & Web3:

• Master cutting-edge technologies and become an expert in the most innovative industry.

Work with the Fintech of the Future:

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

Take Your Professionalism to the Next Level:

• Gain unique experience and be part of global transformations.

Drive Innovations:

• Influence the industry and contribute to groundbreaking solutions.

Join a Strong Team:

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

Work-Life Balance & Well-being:

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

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

Let’s Build the Future Together!

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.

Join an exciting journey to build and scale a global Media Data Foundation for a leading global organization based in Europe. This platform brings together paid media, digital analytics and marketing performance data from dozens of advertising and measurement platforms. It unlocks reliable media reporting, marketing ROI measurement and data-driven investment decisions across markets.

As a Middle Data Engineer, you will play a pivotal role in shaping and implementing the platform's architecture. The focus is on hands-on technical execution and collaboration with cross-functional teams.

Your work will turn raw media and marketing data into trusted, harmonised data products used by marketing, media and analytics teams around the world. You will use modern tools to solve complex challenges, working alongside skilled architects, engineers and business stakeholders.

Key Responsibilities:

• Hands-On Development: Build, maintain and optimize data pipelines for ingestion, transformation and delivery of media data (Meta, Google Ads, DV360, TikTok, The Trade Desk, GA4, CM360 and others).
• Create and implement scalable solutions to handle many data sources, frequent API and schema changes, and high volumes of data.
• Data Modeling & Warehousing: Design and maintain efficient, harmonised data models for cross-platform media reporting in Snowflake.
• Lead the move of transformation logic to dbt, including orchestration, testing, documentation and CI/CD.
• Collaboration: Partner with Solution Architects to translate high-level designs into detailed implementation plans.
• Work closely with Technical Product Owners, media agencies and market teams to align data solutions with business needs.
• Platform Development: Enable data readiness for media dashboards (Power BI), marketing mix modelling / ROI analytics and campaign taxonomy governance.
• Implement robust frameworks to monitor data freshness, completeness, quality and pipeline performance, with automated alerting.
• Security & Compliance: Implement robust access controls and data protection across the pipeline and for data shared with internal and external consumers.
• Ensure compliance with data privacy regulations (e.g. GDPR, CCPA) and internal data governance policies (data product tiers, tagging, naming standards).
• Monitor and address potential vulnerabilities, including service account and secret management, ensuring the platform follows security best practices.

Requirements:

• 2+ years of experience showing technical expertise and critical thinking in data engineering.
• Hands-on experience with dbt and strong Python programming skills.
• Proficiency in Snowflake and strong expertise in data modeling are essential.
• Demonstrated experience with marketing, media or advertising data (ad platform APIs, campaign hierarchies, web analytics) is required.
• In-depth understanding of security and governance in Snowflake: RBAC, secure views, data sharing, masking and row access policies, object tagging.
• Ability to design, implement and promote solution patterns and standards for complex, multi-source data platforms.
• Familiarity with multiple cloud platforms (Azure or GCP preferred, with a focus on Azure, including ADF).
• Experience with ETL/ELT and data integration tools (Adverity, Fivetran or similar) and batch orchestration.
• Competence in SQL, relational database design and efficient methods for data retrieval and preparation at scale.
• Proven ability to collect and process raw data at scale, including scripting, REST API integration and SQL querying.
• Experience with BI tools (Power BI preferred) and supporting reporting consumers.
• Experience working in global environments and collaborating with virtual teams and external agencies.
• A Bachelor's or Master's degree in Data Science, Computer Science, Economics or a related discipline.

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 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’re looking for a GCP data engineer with 4+ years of experience who can work independently across multiple client projects. Middle-level candidates are welcome, senior level is not required. The role involves working in US time zones.
 

Must-have skills

• Advanced BigQuery SQL, including scheduled queries, data transfers and incremental loads
• Python
• GCP services: Cloud Run, Cloud Scheduler, Cloud Functions, Secret Manager, IAM and Monitoring, managed across many projects at the same time
• REST APIs, webhooks and SFTP
• Git and Docker
• LLM APIs (OpenAI, DeepSeek, Perplexity) and prompt writing
   

Nice to have

• Terraform
• n8n
• Supabase and Postgres
• Clay
• Google Meridian
• Experience in lead scoring or marketing tech
• Experience optimizing GCP and LLM costs

Our Customer:

Our customer is a technology company developing data-driven solutions for digital advertising and real-time campaign optimization. The team works with large-scale data and Machine Learning to support automated advertising decisions and improve campaign performance.

Your tasks:

• Develop, improve, and operate ML models used in production advertising systems.
• Work on ML problems related to bidding, bid optimization, and real-time advertising decision-making.
• Develop models for CTR/CVR prediction.
• Optimize campaign performance, budget allocation, and pacing.
• Work on ranking and decisioning models for advertising systems.
• Analyze large-scale advertising data and identify opportunities for optimization.
• Translate business and advertising problems into practical Data Science / ML solutions.
• Evaluate model performance and business impact using relevant advertising KPIs.
• Conduct experiments and A/B testing to validate and improve ML solutions.
• Collaborate with engineering and product teams to deploy and continuously improve production models.

Required experience and skills:

• 5+ years of commercial experience in Data Science / Applied Machine Learning.
• Hands-on experience in AdTech / Programmatic Advertising.
• Direct experience with RTB / real-time bidding systems.
• Commercial experience applying ML/Data Science to advertising optimization.
• Hands-on experience with bidding or bid optimization.
• Experience with CTR/CVR prediction, campaign optimization, ranking, pacing, budget allocation, or advertising decisioning.
• Experience developing, improving, or operating ML models in production.
• Strong Python skills.
• Strong SQL skills and experience working with large-scale datasets.
• Experience translating business problems into ML/Data Science solutions.
• Strong analytical and problem-solving skills.
• Strong English communication skills.

Would be a plus:

• Experience with DSP platforms.
• Experience with bidder logic, bidding algorithms, or bid-price optimization.
• Knowledge of OpenRTB and auction dynamics.
• Experience with real-time decisioning or pre-bid optimization/filtering.
• Experience with user acquisition, retargeting, or performance advertising.
• Experience with large-scale real-time ML.
• Experience with online experimentation / A/B testing.
• Experience with contextual bandits, online learning, or reinforcement learning.

Our team is seeking a Data Solution Architect to further strengthen our capabilities.

Responsibilities

• Work closely with business in identifying solution requirements and key case-studies/scenarios to architect Data solution
• Participate in Data and Big Data initiatives on a company level
• Design Data analytics solutions by utilizing the Data technology stack with Big Data techniques
• Conduct solution architecture review/audit, calculate and present ROI
• Create and present solution architecture documents with deep technical details to customer and implementation teams
• Participate in specific “pre-sale” activities related to available experience and practice in order to prepare technical proposals on customer requests
• Lead implementation of the solutions from establishing project requirements and goals to solution "go-live"
• Maintain a strong understanding of technical solutions and architecture design trends and best practices, stay on cutting edge of Data technologies
• Constantly grow expertise by gathering and monitoring available EPAM project experience and ongoing projects with clients from different business domains to drive further EPAM business in Data field
• Create and follow personal education plan in the technology stack and solution architecture
• Share experience, knowledge and vision with EPAM, colleagues and customer teams. Participate in seminars, meet ups, mentoring, training programs. Prepare white papers and presentations

Requirements

• Strong ‘hands-on’ experience as a Data Architect with design/development background with Java, Scala, or Python
• Architecture experience and practice in Data Management, Data Storage, Data Visualization, Disaster Recovery, Integration, Operation and Security
• Experience with building traditional Cloud Data Warehouses, Data Lakes
• Knowledge of high load and IoT Data Platform architectures and infrastructures
• Wide experience in analysis, design, implementation, deployment as well as troubleshooting and rebuilding distributed Linux based platforms and Big Data solutions on premises and in Cloud
• Strong Cloud experience in at least one of the Cloud providers (AWS, Azure, GCP)
• Solid experience in continuous delivery tools and technologies
• Broad experience with Containers and Resource Management systems: Docker, Mesos, Kubernetes/OpenShift, Yarn
• Able to deliver Data Analytics projects and architecture guidelines
• Strong in research, comparison, and selection of tools / technologies / approaches to be used
• Practical experience in performance tuning and optimization, bottleneck problem analysis
• Strong communication skills, experienced in team coordination skills and solution implementation supervision
• Good in Agile development methodology, Scrum in particular
• Solid skills in business analysis, network/stack architecture, troubleshooting, support
• Fluent English

As a member of Computer Vision Team, you will contribute to data preparation, research, prototyping, and the deployment of machine learning models and computer vision algorithms in edge and cloud environments. Your responsibilities will also include monitoring and evaluating solution performance in production and adapting the system to rapidly changing operational conditions.
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
• Knowledge of C++