Jobs Data Science

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.

Project description

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

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

Necessary skills

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

Would be a plus

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

Responsibilities

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

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

   

Proposed:

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

Job Description

• Master’s degree in Computer Science, Data Science, Applied Mathematics, or a related field.
• 8+ years of professional experience in machine learning, data science, or AI engineering.
• Proven experience as a technical lead or solution architect for ML/AI projects, with accountability for end-to-end delivery in a production environment.
• Strong proficiency in Python and the modern ML/AI ecosystem (e.g., PyTorch, Hugging Face, LangChain/LangGraph, Scikit-learn).
• Hands-on experience with data ingestion, RAG pipeline optimization, model evaluation, deployment (MLOps), and monitoring.
• Deep understanding of generative AI (LLMs, embeddings, RAG, prompt engineering, and agentic reasoning) and its practical constraints (latency, cost, safety, hallucinations).
• Experience turning complex business needs into "machine-ready" technical specifications and acceptance criteria.
• Strong experience with major cloud platforms; hands-on knowledge of AWS (e.g., Amazon Bedrock, SageMaker) or GCP (e.g., Vertex AI) is highly desirable.
• Evidence of using modern GenAI tools (Claude Code, GitHub Copilot, etc.) to significantly accelerate your development and testing process.

Job Responsibilities

Advanced Recommendation Modeling: Design and deploy recommendation algorithms that account for time-decay, breaking news signals, and short-term user intent, distinguishing them from long-term preference models used in streaming.
Generative AI Integration: Lead the development and integration of Gen AI and LLM-based models to enhance content summarization, semantic search, and personalized news briefings.
Signal Processing: Engineer complex feature sets that weigh recency, topic sensitivity, and contextual relevance (e.g., differentiating between a user following a specific stock ticker vs. a general sector interest).
Model Lifecycle Management: Own the end-to-end lifecycle of ML models, from hypothesis and training to A/B testing, deployment, and monitoring in a high

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

Responsibilities

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

Requirements

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

Preferred Qualifications

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

Why PredictSpring?

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

We are looking for a Senior Data Scientist to help build data-driven products that significantly improve customer experience on a large-scale betting platform. You will work on high-impact machine learning models, take full ownership from research to production, and directly influence product and business decisions. This role goes beyond modeling – you will deploy models into production, run experiments, monitor results, and partner closely with product and business teams.

You will work on models and systems such as:

• Churn, retention and LTV prediction;
• Risk scoring, fraud and responsible gambling models;
• Personalization and recommendation systems;
• Uplift and causal models to drive product decision;
• Real-time ML systems powering user experience;

• Experimentation frameworks and A/B testing.

   

What you’ll be doing:

• Design, train and productionize machine learning models for product, risk and personalization use cases;
• Own models end-to-end: data exploration, feature engineering, modeling, deployment and monitoring;
• Design and analyze A/B tests to measure the real business impact of models and product changes;
• Collaborate closely with product managers, engineers and analysts to translate business problems into ML solutions;
•  Monitor model performance, data quality, drift and key business metrics after deployment;

• Communicate insights and recommendations to business and product stakeholders.

   

What we’re looking for:

• 4+ years of experience as a Data Scientist or in a similar applied ML role;
• Strong hands-on experience with Python and SQL;
• Proven experience building and deploying ML models in production;
• Experience with churn, LTV, behavioral or risk-related models;
• Solid understanding of statistics, experimentation and A/B testing;
• Ability to clearly explain technical results to non-technical stakeholders.

Nice to have:

• Experience in gaming, fintech or other high-scale consumer products;
• Experience with recommendation systems or risk/fraud models;
• Familiarity with cloud environments and basic MLOps practices;
• Experience working with real-time or near real-time ML systems.

Who We Are:

We are DATA.BET, a product IT company that develops comprehensive technological solutions for sports, esports, and virtual sports betting in a single sportsbook.
Our key products - Odds Feed, AI-powered risk management system, and fast Single Page Application - help partners gain stable profits and a competitive advantage.
Our team consists of more than 250 professionals. 

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

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

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

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

Job Responsibilities:

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

Requirements:

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

Skills:

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

Nice to have:

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

What We Offer:

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

Role Overview

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

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

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

Key ResponsibilitiesStrategy Development

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

Engineering & Deployment

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

Market Microstructure & Execution

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

RequirementsHard Requirements (Must-have)

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

Nice to Have

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

Academic Background

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

What We’re Looking For

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

Compensation

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

What We Offer

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

Hiring Process

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

We are looking for an experienced Data Scientist for a full-time job to join our team.


Requirements:
- 2+ years of experience as a data scientist
- BSc in Mathematics, Statistics, Computer Science, Economics, or another related field.
- Experience in using Python & SQL
- Experience with Airflow and GCP
- Experience with Git & CI/CD
- Upper Intermediate English — written and spoken
- Ability to design creative solutions for complex requirements
- Ability to learn and lead projects independently, and to work with minimal supervision with customers (tech & business)

Responsibilities:
- Conduct independent research, including defining research problems, creating research plans, designing experiments, developing algorithms, implementing code, and performing comprehensive comparisons against existing benchmarks;
- Clearly communicate your research findings to both technical and non-technical audiences
- Work on various data sources and apply sophisticated feature engineering capabilities
- Bring and use business knowledge
- Build and manage technical relationships with customers and partners.

We offer:
1) Paid vacation and sick leave 

2)We provide the equipment you need to work comfortably (if required)

3)We cover 50% of courses if you want to grow professionally 

4)Regular salary reviews based on your performance 

5) Competitive salary, depending on your experience 

6) Always on-time payments — no delays 

7)A normal, supportive team without unnecessary bureaucracy 

We are looking for an experienced Data Scientist for a full-time job to join our team.


Requirements:
2+ years of experience as a data scientist
BSc in Mathematics, Statistics, Computer Science, Economics, or another related field.
Experience in using Python & SQL
Experience with Airflow and GCP
Experience with Git & CI/CD
Upper Intermediate English — written and spoken
Ability to design creative solutions for complex requirements
Ability to learn and lead projects independently, and to work with minimal supervision with customers (tech & business)

Responsibilities:
Conduct independent research, including defining research problems, creating research plans, designing experiments, developing algorithms, implementing code, and performing comprehensive comparisons against existing benchmarks;
Clearly communicate your research findings to both technical and non-technical audiences
Work on various data sources and apply sophisticated feature engineering capabilities
Bring and use business knowledge
Build and manage technical relationships with customers and partners.

We offer:
12 sick leaves and 18 paid vacation business days per year
Comfortable work conditions (including MacBook Pro and Dell monitor on each workplace)
Smart environment
Interesting projects from renowned clients
Flexible work schedule
Competitive salary according to the qualifications
Guaranteed full workload during the term of the contract
Corporate leisure activities
Game, lounge, sport zones.

We are seeking a data integration specialist with expertise in Connex mainframe data integration tools. The role involves designing, building, and maintaining data flows between mainframe and enterprise systems, ensuring data quality and consistency, optimizing extraction and transformation processes, and supporting ongoing reporting and compliance needs.

Requirements

• 3–5+ years of experience working with Connex data integration solutions in a mainframe (z/OS) environment.
• Solid understanding of file handling, JCL, batch processing, and job scheduling.
• Experience with data mapping, transformation logic, and cross-platform data movement.
• Familiarity with relational databases and modern integration patterns (MQ, APIs, flat file exchanges) is a plus.

• English level: B2—C1.

   

Key Responsibilities

• Design, build, and maintain data integration flows between mainframe and enterprise systems
• Ensure data accuracy, consistency, and integrity across all integrated systems
• Develop and optimize data extraction, transformation, and loading processes
• Work with mainframe environments (z/OS), including file handling and batch processing
• Create and maintain JCL scripts and manage job scheduling processes
• Implement and maintain data mapping and transformation logic
• Support reporting processes and ensure compliance with data standards
• Monitor and troubleshoot data integration workflows and resolve issues
• Collaborate with internal teams to support data exchange and integration needs

We are looking for a Senior Data Scientist to join an international Ad-Tech company working with high-load RTB systems processing over 2 billion requests daily.

This role is ideal for someone with strong production experience in Ad-Tech environments, deep understanding of real-time bidding ecosystems, and hands-on work with large-scale machine learning systems.

Requirements:

• 5+ years of commercial experience in Data Science / Machine Learning
• Strong hands-on experience in Ad-Tech - MUST HAVE
• Solid understanding of RTB ecosystems, bidding algorithms, auctions, DSP/SSP flows
• Experience working with high-load distributed systems and large-scale datasets
• Production experience with ML models in real-time environments
• Strong Python skills
• Experience with SQL and large data processing frameworks
• Experience with experimentation, A/B testing, performance optimization
• Understanding of recommendation systems, prediction models, user behavior analytics, or bidding optimization
• Experience with cloud platforms and data pipelines is a plus
• Upper-Intermediate+ English

Responsibilities:

• Develop and improve ML/Data Science solutions for RTB and Ad-Tech products
• Work with large-scale real-time data streams and optimize bidding performance
• Build, test, and deploy production-ready ML models
• Analyze user behavior, traffic quality, campaign performance, and auction dynamics
• Collaborate with engineering and product teams on scalable ML infrastructure
• Improve prediction accuracy, targeting, and monetization efficiency
• Participate in architecture and optimization discussions for high-load systems

Nice to have:

• Experience with recommendation systems or ranking models
• Knowledge of ClickHouse, Kafka, Spark, Hadoop, or similar technologies
• Experience with deep learning / reinforcement learning in Ad-Tech
• Experience with fraud detection or traffic quality analysis

If you have strong Ad-Tech expertise and experience with RTB systems at scale - we’d be happy to connect 🚀

Junior Data Scientist/Quant Researcher Internship — 
Your Entry Point Into the World of High-Frequency Trading

Are you passionate about data analysis? Do you thrive on competitions, love solving unconventional problems, and want to test yourself in an industry where every nanosecond counts?

Join us for a paid internship at Atto Trading — an American HFT firm that builds high-frequency trading algorithms for U.S. financial markets.

💼 About Atto Trading — Where Engineering Meets Finance

Atto Trading is an American tech-driven trading company that builds and runs high-frequency, algorithmic strategies on financial markets.
 

We’re a small, focused team of engineers, traders, and researchers who:

• 💡 Turn ideas into profitable strategies
• 🇺🇸 Operate on U.S. financial markets
• 🧠 Constantly learn and tackle hard technical challenges together
• 🛠 Build ultra-fast, rock-solid software
   

As an intern, you won’t be stuck on side tasks — you’ll be a real part of the engineering team from day one.

🧠 During the internship, you will do:

• Analyze large datasets of market data using Polars, SQLAlchemy, scikit-learn, etc
• Build ipynb reports and interactive visualizations using Bokeh or Shiny-Plotly that provide real value
• Work with private analytical tools to create pipelines for subindicator generation
• Collaborate with engineers, traders, and analysts in a real-world business environment
   

📌 Program Details

• 🗓 Duration: 4 weeks, summer (August)
   
• 📍 Location: Ukraine in-office (Lviv) 
   
• 💼 Format: Paid internship
   
• 🏆 One top-performing intern will be offered a full-time or part-time role (depending on academic commitments)
   
• 🎁 The selected intern will receive an iPad as part of the welcome package from Atto Trading
  
   

This is a unique opportunity to gain real-world experience in high-frequency trading (HFT) — where analytics, precision, and speed determine success.

Please note: This internship is intended for candidates located in Ukraine. 

Please briefly describe your key achievements (academic, project-based, volunteer, or personal) in your CV.

About us:
Gismart is a value-driven mobile app developer with a strong presence in the Health & Wellness, Utilities, and Music app markets. We have achieved a significant milestone of over 1 billion downloads worldwide, taking a step toward our mission of cultivating the well-being of people worldwide. With headquarters in London, UK, Gismart is a dynamic global company with a reach extending across Europe and far beyond. Our determined team comprises over 300 individuals who bring diversity, creativity, innovation, and relentless drive to the company. Gismart unites professionals from diverse backgrounds in entertainment, music, and tech, allowing us to play to each other’s strengths and succeed as a team.

Our mission:
Become a stepping stone on our customers’ journeys of self-improvement.

Our values:

• Deliver what matters
• Respect and support others
• Initiate and own
• Voiceopenly
• Execute with quality

If you are passionate about mobile app development and want to join a company that’s reshaping the industry, Gismart is the place for you. We provide exciting career opportunities, a supportive workplace culture, and the chance to contribute to a team that is making a tangible impact. For more information on Gismart, visit gismart.com.

Responsibilities:
 

• Work on subscription/ads/in-app LTV prediction services
• Ensure efficiency, reliability, explainability and observability in ML pipelines
• Build and maintain ETL workflows, querying large tables
• Detect anomalies, data drifts, prediction shifts; partner with User Acquisition managers on investigations
• Collaborate with data engineers on data quality issues detection
• Participate in generative AI projects
   

Requirements:
 

• Hands-on with Machine Learning modelling, good understanding of ML fundamentals
• Proficiency in Python software engineering (parallel/asynchronous computing, unit-testing, CI/CD, etc.)
• Solid grounding in statistics and experimental design
• Advanced SQL, comfort working with large datasets
• Experience with ETL workflows and scheduling pipelines (e.g. Airflow)
   

Would be a plus:
 

• Familiarity with BI tools (Tableau, Power BI, Looker) for data visualisation
• Familiarity with MLOps tools, Databricks platform
• Experience building REST APIs and working with real-time streaming data
• Recommendation systems, NLP/LLMs or other generative AI experience
• Subscription-based product data familiarity
   

Personal qualities:
 

• Proactive and independent — ready to take ownership of projects, drive initiatives, explore new tools and make data-driven decisions without constant supervision
• Excellent communication skills — able to clearly convey tech insights to non-technical stakeholders
• Team-oriented — sharing knowledge, open in communication, active during brainstorming, easy-going
• Business-oriented thinking — interest of how your work impact decisions and product profits
   

Mastery of the following technologies/tools the team uses:

• Python
• Pandas
• SQL
• AWS (Redshift, S3, EC2, RDS)
• LightGBM
• Tableau
• Airflow
• Docker
• LangChain
   

Employee Benefits:

• Remote-First Culture: Our team is diverse and extensive, just like our product portfolio. We provide a flexible working schedule and let you work anywhere in the world, either remotely or in one of our corporate hubs.
• Сoworking Compensation: We provide 100% compensation for coworking spaces in Ukraine (except Kyiv, where we have a cozy and autonomous hub) and 50% compensation for coworking spaces worldwide to make sure that everyone has a comfortable and inspiring workspace.
• Free Office Lunches: We want you to stay fueled and focused, so we provide delicious free lunches for everyone working from our hubs. It’s one less thing for you to worry about during a productive workday.
• Public Holidays Policy: Gismart observes public holidays based on the Ukrainian or Polish holiday calendars. Employees working in other locations are entitled to 12 public holidays per year.
• 100% Sick Leave Compensation
• Mental and Physical Health: To help you stay happy and healthy, Gismart will partially cover your medical insurance, sports activities, and therapy costs.
• Personal Equipment Policy: Of course, we’ll provide you with all the equipment you need or cover the maintenance cost for your own tools.
• Personal Learning and Development: We love to see you learn and grow, so Gismart will cover 70% of your professional development courses. We’ll also pay for 100% of corporate English courses.
• Time-Off Policy: Every employee gets 18 working days of paid vacation and 3 personal days per year, with an extra day added for each year at Gismart.
• Corporate Events: We are remote-first, but we love meeting up in person. Whenever possible, we organize corporate events and team-building activities across all Gismart hubs.

We're seeking an exceptional Data Architect to lead data storage strategy and design across our multi-product SaaS platform as we unify independent products into a coherent platform. This role combines strategic leadership with hands-on technical expertise—you'll shape our data architecture vision while getting into the details during implementation and troubleshooting.

Key Responsibilities: 
•⁠ ⁠Drive data architecture unification across multiple SaaS products, creating coherent patterns while respecting product needs.
•⁠ ⁠Partner with vertical technical leads to provide horizontal architectural support and alignment.
•⁠ ⁠Design and optimize data storage across multiple technologies—AWS OpenSearch/Elasticsearch, relational databases, S3, NoSQL, and data warehousing.
•⁠ ⁠Optimize for performance and resilience— indexing, querying, high availability, redundancy, and disaster recovery at scale.
•⁠ ⁠Support AI initiatives—partner with our AI specialist team on data architecture for AI capabilities.
•⁠ ⁠Bring clarity from ambiguity—translate complex challenges into clear architectural direction.
•⁠ ⁠Build capability, not dependencies—mentor engineers so teams become more self-sufficient.
•⁠ ⁠Balance performance, cost, and reliability across our platform.

Qualifications:
•⁠ ⁠Deep expertise in AWS OpenSearch/Elasticsearch—you've solved hard problems at scale with indexing, querying, and performance.
•⁠ ⁠Broad data technology experience—relational databases (e.g. PostgreSQL, MySQL, RDS), object storage (S3), NoSQL (e.g. DynamoDB, MongoDB, Redis), data warehousing.
•⁠ ⁠Cloud and container knowledge—AWS preferred (Azure/GCP also valued); understand stateful services in Kubernetes.
•⁠ ⁠Proven platform architecture experience—track record of driving technical strategy across multiple teams or products at scale.
•⁠ ⁠Senior-level maturity—you make those around you better through mentorship and capability building.
•⁠ ⁠Influence without authority—you work effectively across teams, bring clarity from ambiguity, and think strategically.
•⁠ ⁠SaaS experience—comfortable with multi-tenant environments and operational excellence.

Location: EU or Ukraine
Type: Fulltime 
Start: ASAP

On behalf of our client, we are looking for a Senior Machine Learning Engineer

Requirements:

- Strong proficiency in Python, TensorFlow, PyTorch, scikit-learn

- Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools

- Deep understanding of NLP, Computer Vision, or Recommendation Systems

- Solid knowledge of data structures, algorithms, and distributed computing

- Strong problem-solving, leadership, and communication skills

Nice to have:

- Experience leading ML projects end-to-end

- Background with big data technologies (Spark, Hadoop)

- Experience with ethical AI and bias mitigation

Location: Malmö, Sweden

Company offers:

- Long-term employment with possibilities for professional growth

- Fully remote work

- Reasonably flexible schedule

- 15 days of paid vacation

- Regular performance reviews