Jobs Data Science

The product we are working on is one of TOP-3 navigation systems, complex web-services and other solutions related to it. The web and mobile apps handle information at massive scale and extend well beyond the search giving people and companies a lot of new useful options.

As a Data Science Infrastructure Software Engineer, you will play a high-impact role within a small, efficient team dedicated to bridging the gap between Engineering and Data Science. Your work will focus on building cutting-edge Generative AI infrastructures and frameworks that significantly boost productivity across the whole product. You will develop tools that bring engineering rigor to data science workflows, solving complex problems in the GenAI space that the market has yet to crack. This is a high-impact role in a small team. You will be working alongside talented engineers and data scientists to build productivity-defining products for the next generation of the application.

Responsibilities:

• GenAI Development: Design, develop, and maintain features for our GenAI analytics agent (DataWhiz) that serve the entire organization for complex data analytical inquiries.
• Framework Optimization: Improve and scale the internal GenAI framework, including fixing bugs and optimizing the core engine for performance and reliability.
• UI/UX Enhancement: Build and implement new UI features for the GenAI chat interface to ensure a seamless experience for internal stakeholders.
• Cross-Functional Collaboration: Partner with development, product, and UX teams to define product requirements, while collaborating with core platform engineers to ensure infrastructure alignment.

• Engineering Excellence: Bridge the gap between Engineering and Data Science by applying software engineering best practices (code reviews, CI/CD, scalability) to DS workflows.

   

Requirements:

• Location in Warsaw
• 5+ years of experience in software development, with a focus on infrastructure or data-centric applications.
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
• Strong proficiency in Python and a solid understanding of backend architecture.
• Experience with SQL and the ability to handle complex data structures.
• Problem-Solving: Ability to write clean, abstract, and maintainable code for a rapidly evolving GenAI landscape.
• Communication: Excellent communication skills for collaborating with geographically distributed teams and translating data science needs into technical requirements.

• Fluency in English.

   

Nice to have:

• Generative AI Expertise: Familiarity with LLM orchestration frameworks, prompt engineering, or vector databases.
• Polyglot Programming: Experience with Kotlin, Java, Bash, or HCL (Terraform).
• Frontend Interest: Experience building chat interfaces or data visualization dashboards.

• Large-Scale Systems: Experience working on large-scale infrastructure that serves a diverse range of internal or external users.

   

We offer:

• Opportunities to develop in various areas;
• Compensation package (20 paid vacation days, paid sick leaves);
• Flexible working hours;
• Medical Insurance;
• English courses with a native speaker, yoga (zoom);
• Paid tech training and other activities for professional growth;
• Hybrid work mode (∼3 days in the office);
• International business trips

• Comfortable office.

   

If your qualifications and experience match the requirements of the position, our recruitment team will reach out to you in a week maximum. Please rest assured that we carefully consider each candidate, but due to the amount of applications the review and further processing of your candidacy may take some time.

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.

Role Type: Contract / Fixed-Scope Consulting Engagement
Duration: 2–3 months (10–12 weeks)
Allocation: Full-time or near full-time (4–5 days/week preferred)
Location: Remote (Must overlap with Spain / CET ± 6 hours)
Languages Required: Spanish (C1+) and English (B2+)
 

The Opportunity

We are looking for a hands-on Senior Data Science / Analytics Engineering Consultant to audit, redesign, and rebuild our core chargeback estimation and revenue estimation models.

This is a critical, end-to-end project. You will turn existing prototypes into production-grade pipelines within our modern data stack (dbt on Databricks & Python). Additionally, you will design and build a lightweight, business-facing scenario tool that enables finance and operations stakeholders to run “what-if” revenue simulations.

Our Technical Philosophy: Parsimony Over Black Boxes

We explicitly favor simple, highly interpretable, parametric approaches. If your first instinct for a forecasting problem is to throw an XGBoost ensemble, a deep learning model, or an LLM at it, this is not the project for you.

We build models where every parameter carries an explicit business meaning that can be explained to non-technical stakeholders in plain language (e.g., “If price increases by 10%, conversion drops by X% because our calculated price elasticity is −1.3”).
 

Scope of Work & Deliverables

• Phase 1: Discovery & Audit (Weeks 1–2): Review current estimation models (assumptions, dbt lineage, validation methods). Reconcile historical model outputs against actual accounting figures for the last 12–24 months to quantify bias and error. Deliver a written findings report.
• Phase 2: Redesign (Weeks 3–4): Propose the target parametric methodology for each model (granularity, refresh cadence, uncertainty quantification) and secure stakeholder sign-off.
• Phase 3: Rebuild (Weeks 5–9): Productionize the new models in dbt, Databricks, and Python. Use curve-based formulations with fitted historical parameters and clear confidence intervals. Implement strict unit/dbt testing and MLflow tracking.
• Phase 4: Scenario Tool (Weeks 9–10): Build a lightweight business interface (e.g., Streamlit on Databricks or a parameterized Databricks SQL dashboard). Users must be able to input hypotheses (price ±X%, volume ±Y%, mix shifts) and instantly view projected net impact with uncertainty bands.
• Phase 5: Handover (Weeks 11–12): Conduct knowledge transfer sessions, deliver runbooks/model cards, and provide a 2-week post-handover bug-fix support window.
   

Your Profile

• Experience: 5–8+ years in Data Science, Quant Analytics, or Senior Analytics Engineering.
• Production Ownership: Proven track record of owning financial-estimation or forecasting models in production end-to-end.
• The “Parsimony” Mindset: Demonstrable expertise in parametric/curve-based modeling (price elasticity, cohort survival curves, demand curves, GLMs) over black-box ML.
• Stakeholder Tooling: Experience building clean “what-if” tools or financial planning interfaces for business leadership.
• The Stack: Advanced Python (pandas, numpy, scikit-learn, statsmodels, and/or scipy.optimize), production dbt (incremental models, snapshots, tests), and Databricks (PySpark, Delta, workflows).
• Domain Knowledge: Direct experience in payment risk, chargebacks, refund/dispute modeling, revenue forecasting, cohort LTV, or pricing analytics.
• Communication: Exceptional ability to cross-reference data science outputs with strict financial accounting figures.
• Languages: Spanish (C1+) is mandatory for daily synchronization with local finance/ops teams; English (B2+) is required for technical documentation.
   

Nice to Have

• Background in FinTech, subscription models, payments, or high-volume e-commerce.
• Deep familiarity with Unity Catalog, Databricks Workflows, or Airflow.
• A strong track record of successful independent consulting engagements (references requested).

We are looking for a Senior AI/Machine Learning Engineer to join a healthcare project from the Netherlands focused on simplifying preparation for orthopedic surgeries. The product uses artificial intelligence to automatically analyze 3D images of the skeletal system and support surgical planning. In this role, you will focus on continuing and improving the X3D pipeline (X-ray to 3D bone reconstruction) and integrating it into the web application.
 

Requirements:
— 5+ years of commercial experience in Machine Learning/AI engineering.
— Proven commercial experience working on medical imaging or healthcare-related projects is a must.
— Strong experience with PyTorch and deep learning model training, evaluation, and optimization.
— Solid background in medical image analysis (CT, X-ray) and/or 3D computer vision.
— Strong understanding of image processing fundamentals, including registration, segmentation, and data augmentation techniques.
— Familiarity with GAN architectures (Pix2Pix, CycleGAN) and encoder-decoder networks.
— Experience working with medical imaging file formats (NIfTI, DICOM).
— Ability to read and implement techniques from research papers.
— Proficiency in Python and scientific computing libraries (NumPy, SciPy, SimpleITK or similar).
— Self-directed and independent working style with the ability to effectively collaborate under technical guidance.
— Upper-Intermediate or higher level of English (spoken and written).

Nice to have:
— Experience with 3D shape reconstruction or 3D mesh processing.
— Familiarity with DRR generation from CT volumes.
— Experience with Azure ML or similar cloud ML platforms.
— Background in orthopedic or musculoskeletal imaging.
— Experience in a medical device or regulated environment (FDA, CE).

Responsibilities:
— Improve and extend the existing X3D pipeline for X-ray to 3D bone reconstruction.
— Design, train, evaluate, and optimize deep learning models for medical image analysis and 3D reconstruction tasks.
— Work with medical imaging data (CT, X-ray, DICOM, NIfTI) and implement preprocessing, augmentation, segmentation, and registration techniques.
— Research, prototype, and implement new approaches from academic papers and industry best practices.
— Integrate machine learning solutions into the web application and support deployment workflows.
— Collaborate closely with the Head of Engineering to further develop and productionize the existing AI pipeline.
— Maintain code quality through testing, documentation, and continuous improvement of ML infrastructure and development processes.

Interview stages:
— HR interview (30 minutes).
— Technical interview (1 hour).
— Interview with the customer (1 hour).
— Job offer 🎉🎉🎉

We offer:
— Competitive salary.
— Challenging tasks and projects.
— Opportunities for professional development and growth.
— Flexible working hours.
— New hardware.
— Free English lessons.
— Table tennis and yoga classes.
— Availability of generators and Starlinks in the office.
— Small gym in the office.
— Adjustable height tables.
— Regular office fruit delivery and other benefits.

Let’s create value together!

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

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

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

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

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

We offer:

• Great networking opportunities with international clients, challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary nominated in USD;

• Paid vacation and sick leaves;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

Mine Marketing is a digital marketing company. We’re looking for a Technical Data & Automation Specialist to join our team and work closely with leadership on data, automation, system development, troubleshooting, and production operations.


Role Requirements:
 

• Required: Proven experience leveraging AI development tools such as Claude Code to build solutions, investigate issues, develop automations, optimize systems, and accelerate end-to-end development workflows
• Strong SQL skills, including writing complex queries, optimization, and performance analysis
• Experience working with Data Pipelines and ETL processes
• Experience working with production systems and investigating complex technical issues
• Experience working with APIs and system integrations
• Familiarity with PostgreSQL
• Experience with AWS or GCP is a plus
• Experience with Meta Ads, Google Ads, or marketing/ad-tech systems is a significant advantage
• Experience building automations and operational workflows
• Strong understanding of end-to-end (E2E) development, from requirements and solution design through implementation, deployment, and maintenance

Personal Qualities:
 

• Strong analytical and problem-solving skills
• Fast learner with the ability to quickly understand complex systems
• Highly independent and capable of taking ownership of tasks
• Exceptional attention to detail
• Strong organizational and time-management skills
• Ability to work accurately under pressure in a fast-paced environment
• Ability to prioritize and manage multiple responsibilities simultaneously

• Proactive mindset with a strong sense of accountability
  
  
  What we offer:
  - Opportunities for professional development and personal growth 🚀

  - Competitive salary, reasonable and fair working conditions 💵

  - A ridiculously awesome team and work environment 🎉

  - Training opportunities, including paid courses and webinars 💻

  - Remote working conditions 🏠

  - Generous PTO and Holidays 🌴
  
  Join us and let's make some social media magic happen! Apply now!

About the company: United Tech is a global IT product company shaping the future of real-time social connection. With millions of users across North America, Europe, LATAM, and MENA, we build next-gen mobile and web apps for live-streaming and social networking. Our platforms enable connection at scale fast, interactive, and deeply engaging. The market is projected to exceed $206B by 2030, and we are already leading the evolution. Founded in Ukraine, scaling worldwide
 

About your role: In this role, you will directly influence product growth and monetization by improving Recommendation Systems for gifts and coins. You’ll work end-to-end on ML solutions — from defining the Data Science roadmap and running experiments to deploying production-ready models — while collaborating closely with Product Managers, Analysts, and Engineers. The role offers a combination of hands-on machine learning, recommendation systems, MLOps, and strategic ownership in a fast-paced product environment where your work will have visible business impact.

In this role, you will

• Create, develop, and improve machine learning models to enhance business performance and product effectiveness
• Collaborate closely with cross-functional teams, including Product Managers, Analysts, and Engineers, to deliver innovative ML-driven features and improvements
• Apply expertise in machine learning algorithms, data structures, and optimization techniques to improve model accuracy, scalability, and efficiency
• Implement and maintain MLOps best practices for model deployment, monitoring, retraining, and maintenance in production environments
• Investigate, troubleshoot, and resolve technical issues related to machine learning models, data pipelines, and infrastructure
• Stay up to date with the latest advancements, technologies, and best practices in machine learning, artificial intelligence, and data science

It’s all about you

• 4+ of Machine learning and deep learning on tabular data, Recommendation systems. 
• 4+ years of software development experience in Python with experience working with ML and DL
• Experience in designing a data science roadmap and the leading technical execution of the project
• Experience with Cloud development AWS/GCP
• Experience of deploy API models on Dev/Prod environment
• Practical understanding of A/B tests process
• Practical understanding of the mathematics behind modern machine learning, linear algebra, and statistics.
• Extensive SQL knowledge

What we offer

Care and support: 

• 20 paid vacation days, 15 sick days, and 6 additional days off for family events
• Up to 10 additional days off for public holidays
• 100% medical insurance coverage
• Sports and equipment reimbursement
• Team building events, corporate gifts, and stylish merch
• Maternity recovery support allowance 
• Financial and legal support
• Position retention and support for those who join the Armed Forces of Ukraine
• Participation in social initiatives supporting Ukraine
   

Comfortable working environment:

• Work from our Kyiv hub or remotely with a flexible schedule 
• Modern equipment or depreciation of your own tools
   

Investment in your future:

• Collaborate with a highly-skilled team of Middle & Senior professionals, sharing practical cases and expertise in the social networking niche
• 70% of our heads and leads have grown into their roles here – so can you!
• Performance-oriented reviews and Individual Development Plans (IDPs)
• Reimbursement for professional courses and English classes
• Corporate library, book club, and knowledge-sharing events
   

Hiring process

• Intro call
• Technical Interview
• Final Interview
• Reference check
• Offer

Cloudfresh ⛅️ is a Global Google Cloud Premier Partner, Zendesk Premier Partner, Asana Solutions Partner, GitLab Select Partner, Hubspot Platinum Partner, Okta Activate Partner, and Microsoft Partner.

Since 2017, we’ve been specializing in the implementation, migration, integration, audit, administration, support, and training for top-tier cloud solutions. Our products focus on cutting-edge cloud computing, advanced location and mapping, seamless collaboration from anywhere, unparalleled customer service, and innovative DevSecOps.

We’re currently looking for a Data Engineer/Analyst (GCP) to join our team. In this role, you’ll design, implement, and deliver robust data platforms and analytics solutions on Google Cloud - ensuring technical excellence and client success across the full project lifecycle, from pre-sales discovery to enterprise delivery and internal projects. We’re excited to meet someone who’s ready to make a real impact.

Requirements

- Fluency in Ukrainian
- At least B2 level in English
- GCP Native Data Stack: Deep practical knowledge of BigQuery, Cloud Storage, Cloud Functions, and BigQuery ML.
- 3+ years of experience in Data Engineering
- Strong experience with Dataflow, Dataproc, Pub/Sub, Cloud Composer, or Dataform for building and maintaining optimized ETL/ELT processes in GCP.
- Proficiency in Looker / Looker Studio.
- Advanced SQL (focus on optimization and performance tuning) and Python (for API integrations and pipeline scripting).
- Comfortable in client-facing and pre-sales scenarios (live demos, requirements gathering) with the ability to translate business needs into scalable technical designs.
- A proactive, self-driven approach with high responsibility for data platform reliability and accuracy.
- Familiarity with integrating data from APIs, relational databases, NoSQL systems, and SaaS platforms.
- Ability to work seamlessly with architects, DevOps, and ML engineers to deliver end-to-end cloud solutions.

Responsibilities

- Design and build modern data platforms for enterprise clients, working with both structured and unstructured datasets at scale.
- Lead the implementation of analytics solutions ensuring strict data quality, security, and rigorous performance optimization.
- Run workshops and deliver technical presentations to stakeholders to define and refine data architectures.
- Continuously monitor and tune BigQuery cost/scalability models and ETL performance.
- Collaborate with the team during discovery phases to provide technical expertise, live demos, and solution scoping.
- Identify and explore new GCP features and agentic AI tools to automate operations and improve process analytics.

Work conditions

- Flexible Work Format: Work remotely with flexible hours, allowing you to balance your professional and personal life efficiently.
- Training with Leading Cloud Products: Access in-depth training on cutting-edge cloud solutions, enhancing your expertise and equipping you with the tools to succeed in an ever-evolving industry.
- International Collaboration: Work alongside A-players and seasoned professionals in the cloud industry.
- Expand your expertise by engaging with international markets across the EMEA and CEE regions.
- Vibrant Team Environment: Be part of an innovative, dynamic team that fosters both personal and professional growth, creating opportunities for you to advance in your career.

When applying to this position, you consent to the processing of your personal data by CLOUDFRESH for the purposes necessary to conduct the recruitment process, in accordance with Regulation (EU) 2016/679 of the European Parliament and of the Council of April 27, 2016 (GDPR).
Additionally, you agree that CLOUDFRESH may process your personal data for future recruitment processes. You can withdraw this consent at any time.

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

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

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

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

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

We offer:

• Great networking opportunities with international clients, challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary nominated in USD;

• Paid vacation and sick leaves;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team building activities, corporate events.

We are looking for a Computer Vision Engineer with a solid foundation in classical computer vision and hands-on experience implementing low-level CV algorithms. The ideal candidate will have exposure to SLAM, Visual-Inertial Odometry (VIO), and sensor fusion, with responsibilities adjusted according to experience level.

Responsibilities: 

• Implement and optimize low-level computer vision algorithms under guidance
• Contribute to modules related to feature extraction, tracking, matching, and geometric processing
• Assist in the integration and testing of SLAM/VIO components
• Perform experiments, analyze results, and help prepare reports
• Work closely with senior engineers to explore and apply recent CV research.

Required Qualifications:

• 1+ years of hands-on experience with classical computer vision
• Basic understanding of geometric computer vision principles
• Experience implementing low-level CV algorithms (e.g., filtering, feature detection, camera models)
• Familiarity with SLAM or VIO concepts
• Working knowledge of C++ and Linux
• Ability to learn quickly and navigate recent CV researc
• Degree or ongoing studies in a STEM field.

Nice to Have:

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

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++

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

    Required Qualifications

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

     Key Responsibilities

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

     We offer

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

Dataforest seeks a Data Science Tech Lead/Team Lead 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 Lead/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.

Skills Requirements:

• 5+ years of experience in Data Science\Data engineering field;

• 4+ years of experience with Python;

• Strong management and leadership skills;

• 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/Azure/GCP (Optional);

• Experience in multithreading/multiprocessing approaches;

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

• Previous experience in a Team Lead role;

Key responsibilities:

• Manage Data science department;

• Perform code review, and data scientists assessment;

• Develop DS Architecture;

• Participate in pre-sale 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 offer:

• Great networking opportunities with international clients, challenging tasks;

• Building interesting projects from scratch using new technologies;

• Personal and professional development opportunities;

• Competitive salary fixed in USD;

• Paid vacation and sick leaves;

• Flexible work schedule;

• Friendly working environment with minimal hierarchy;

• Team building activities and corporate events.

Our Enterprise Banking client is enhancing their Regulatory Reporting Value Stream and seeks a strategic Data Steward to own data governance, ensure compliance, and maintain the integrity of critical financial data. You will serve as the primary liaison between business stakeholders and technical teams to ensure data accuracy across products, systems, and processes.

Core Responsibilities

• Data Governance Leadership: Own and drive end-to-end data governance and quality frameworks; ensure full compliance with internal standards and external regulatory requirements.
• Architectural Stewardship: Maintain business glossaries, metadata repositories, and data quality rules; design robust data mappings and transformation logic.
• Requirements Engineering: Translate complex business/regulatory needs into clear functional specifications for engineering teams.
• Quality Remediation: Perform root cause analysis on data quality incidents and coordinate cross-functional remediation efforts.
• Strategic Insights: Develop KPIs and performance dashboards to provide stakeholders with actionable data trends and business intelligence.

What We Need

• Expertise: Significant professional experience in Data Governance, Data Stewardship, or Technical Business Analysis.
• Domain Knowledge: Solid grounding in banking/financial services products and regulatory reporting workflows.
• Technical Proficiency: Advanced SQL skills for large-scale data analysis, profiling, and structural mapping; deep understanding of data warehousing principles.
• Collaboration: Proven ability to act as the "connective tissue" between business units and IT delivery teams.
• Tooling: Proficiency in JIRA, Confluence, and the MS Office suite.

Equals5 helps pharmaceutical companies run precisely targeted ad campaigns on social platforms by identifying healthcare professionals and the consumer signals that reach them. The Identity team builds the data, scoring, and targeting systems that make this possible.

We are looking for a Data Analyst  to join the Identity team at Equals5. This is not a standard analyst role. We are building a dynamic identity resolution system where AI is deeply integrated — both as a productivity multiplier and as a core component of our data processing logic for identity resolution and LLM-based scoring.

We run enrichment against 70+ TB of data, apply AI and LLM-based scoring on top, and process around 20 million enrichment operations per day across hundreds of thousands of records.

The analytical challenges ahead are substantial: how to measure the quality of AI-driven scoring, how to validate that a change makes the system better, how to know where our money and time deliver the most value, and how to turn the questions our internal teams bring in into fast data-backed answers. You will own this side of the business, working daily alongside engineers and the product lead to turn these challenges into decisions that ship.

The main part of the role is not building dashboards — it is the data work that makes a meaningful dashboard possible in the first place. Concretely, you will be:

• Looking at data from multiple vendors side by side and deciding what to trust.
• Reconciling entities across sources that have different shapes and quality.
• Proposing and validating the logic that matches and scores them.
• Defining metrics and ground truth for questions nobody has asked before.
• Tracing why numbers don't line up across partial and sometimes contradictory sources.

Dashboards and visualizations are part of how findings get communicated, but they come at the end — the surface of the work, not its core. Most of your time is spent on what sits underneath: methodology, judgment calls on data quality, and shaping how the domain understands its own numbers.

Responsibilities

• Measurement & Evaluation Foundations: Define how we measure what matters — data quality, the accuracy of our AI scoring, how many records actually get matched to usable signals, cost per outcome. Build the feedback loops that tell us whether a change makes the system better or worse.

• Scoring Intelligence (co-owned with engineers): Partner with the engineering team on the LLM-based scoring system. You will build the evaluation framework for AI scoring, run experiments comparing prompts, models, and approaches against a baseline, and make data-backed calls on where we invest next. Our AI scoring system is actively evolving — you will shape how we measure and improve it.

• Client-related Analysis: Own the analytical side of the work that internal sales and media-buying teams bring in from pharma clients — how reachable a target audience is, how good the data looks, why a campaign performed the way it did. You turn their questions into data-backed answers they can use. Identity is a product core; the analyst works with internal teams, not with clients directly.

• Cost and Value Analysis: Turn cost and value into product decisions. Which data sources and enrichment scenarios pay off, where we overspend, what to cache, what to cut. We operate a mix of free owned data and paid external providers — the decisions have real dollar impact.

• Active AI Usage: Use Claude Code and modern AI engineering tools to multiply your own output. Automate the repetitive parts of analysis so you can focus on the decisions. We provide Claude Code licenses and expect active daily use.

• Data Quality Response: When pipeline output drifts, a provider degrades, or upstream data shifts, you notice first, diagnose the root cause, and drive the fix. You treat data quality as a product, not a ticket queue.

Requirements

• 5+ years as a Data Analyst, Analytics Engineer, or Data Scientist in a product team (not consultancy, not BI-only roles).
• Advanced SQL at TB scale — BigQuery, Snowflake, or equivalent warehouse. You can read and write complex queries on tens of terabytes without someone pre-modelling the data for you.
• Python for analysis at a working level — pandas, Jupyter, or modern equivalents. Comfortable putting together a small script or helper when an existing tool doesn't cover your case.
• Built measurement or evaluation frameworks from scratch for systems that had no baseline. You are comfortable defining what and how to measure, not consuming someone else's KPI.
• Comfort with probabilistic systems. You understand that noise is inherent and 100% accuracy is not the goal — scoring, matching, ranking.
• AI-native workflow. You already use Claude Code, ChatGPT, Copilot, or similar AI tools daily and integrate them into your analytical process.
• English: B2+ (Upper-Intermediate) or higher.

Strong plus 

• LLM evaluation experience — A/B testing AI-powered features, output scoring, prompt iteration with measurable outcomes.
• Identity resolution / identity graph experience — adtech, martech, or customer data platform context (LiveIntent, LiveRamp, Epsilon, Experian Marketing, Acxiom, Merkle, or similar).
• Healthcare or pharma data — working with NPI, HCP-level data, healthcare taxonomies, pharma targeting.

Nice to have

• Experience running controlled experiments on data pipelines.
• Prompt engineering or structured LLM prompt design.
• Prior work in AI-first product companies.

What We Offer

• Fully remote with flexible hours, with working overlap in CET ±2 hours for syncs.
• AI-Native Environment: We provide licenses for Claude Code and encourage using the bleeding edge of AI tech — both for daily work and as part of product logic.
• High-Impact Role: You will directly shape how we identify, score, and reach healthcare professionals — the core business of our domain.
• Small team, direct impact: You will work directly with Product and Engineering leads — no layers between you and the people making decisions.
• No Bureaucracy: Fast decisions, no legacy processes, focus on results.