Jobs Data Science

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.

BETER is an international product group of companies operating in the B2B segment, specializing in fast sports and esports tournaments and technological solutions for their distribution.

BETER is the exclusive rights holder of tournament products, broadcasting rights, and official data, and ensures their organization through professional tournament operators, including Setka Cup and ESportsBattle, which conduct official sports and esports events in accordance with established standards and under the auspices of relevant federations and regulatory requirements.
 

We are looking for a Data Scientist who is eager to proactively identify opportunities to improve and automate our business using data science and machine learning. You will work within a small, dedicated team of data scientists collaborating closely with backend engineers, other departments, and end users, while being part of a larger ecosystem of trading and technology experts.

In this role, you will design, develop, and optimize predictive models, implement anomaly detection systems, and participate in building production-grade machine learning solutions that directly impact trading and operational processes. You’ll also get hands-on experience with (or apply your existing knowledge of) high-performance architectures, including Kafka, serverless functions, databases, CI/CD pipelines, Kubernetes, and Docker.

Responsibilities:

• Develop and refine mathematical and statistical models for predicting sports and e-sports outcomes.
• Communicate with end users, collect feedback, and build technical solutions based on it.
• Apply machine learning to improve trading strategies, automate workflows, and detect anomalies.
• Proactively identify opportunities to use data science for business optimization and process automation.
• Perform large-scale historical data analysis to generate insights and improve model performance.
• Collaborate with backend engineers to build and maintain production machine learning systems.
• Research and prototype new methods for expanding into new sports and markets.

KPIs for This Role:

• Delivery of production-ready machine learning models and pipelines for trading within agreed timelines.
• Improvement in model accuracy and reliability, measured against established benchmarks.
• Reduction of manual intervention in trading workflows through automation initiatives.

Requirements:

• 5+ years of experience in data science, analytics, or a related field.
• Proficiency in Python (pandas, numpy, scikit-learn, etc.) and working with databases.
• Strong knowledge of statistical modeling, probability, and machine learning techniques (Supervised Learning, Unsupervised Learning).
• Experience with XGBoost/LightGBM.
• Experience with large-scale data analysis and building actionable insights.
• Ability to work collaboratively in a cross-functional team and communicate results clearly.
• English level - Upper-intermediate and higher.

Nice-to-Have:

• Experience in the sports or betting industry.
• Experience with PyTorch/Tensorflow.
• Familiarity with real-time data processing (Kafka, streaming systems).
• Exposure to building data pipelines and integrating ML models into production systems.
• Knowledge of advanced ML techniques (e.g., ensemble methods, time-series forecasting, anomaly detection).

We offer:

• Ability to work remotely.
• Competitive and timely payment for services.
• Flexible work schedule.
• Personal mentoring and coaching.
• Team building and corporate events.
• 100% paid sick leave.
• 20 working days of paid vacation.
• Paid child care leave.

BETER is a rapidly growing product company. We create competitive content supplemented with analytics. For more than 5 years, we have been organizing sports tournaments, broadcasts, and developing our own sports community. We hold 45,000+ events per month in esports and traditional sports, and our products are represented in 150+ countries worldwide.

We are looking for a hands-on Data Science Tech Lead to join our team and drive the development of sports analytics and prediction products. This role combines deep technical expertise in machine learning and mathematical modeling with team orchestration and delivery ownership.

You will work closely with the Engineering Manager and lead a team of 4 Data Science Engineers, helping transform business needs and production challenges into scalable data science solutions.

Responsibilities:

• Collaborate with the Engineering Manager to coordinate and support a team of 4 Data Science Engineers
• Collect and analyze business requirements, production issues, and product needs, transforming them into actionable data science tasks and backlog
• Analyze large volumes of sports, esports, and trading data
• Develop and improve sports prediction models using statistics and machine learning techniques
• Conduct, automate, and evaluate data-driven experiments
• Integrate mathematical and ML models into production workflows
• Participate in hands-on development and coding activities
• Perform code reviews and maintain high engineering and data science quality standards
• Ensure efficient execution and delivery of data science initiatives within the team

Requirements:

• Previous experience in a Tech Lead or team leadership role
• Strong hands-on programming skills in Python
• Advanced knowledge of databases and data processing
• Strong expertise in machine learning, statistics, and probability theory
• Experience building and deploying mathematical or predictive models
• Upper-Intermediate+ level of English
• Ability to balance technical leadership with hands-on engineering work

What we’re looking for:

This is primarily a hands-on engineering role. The main focus is building mathematical models, writing production-level code, and delivering real business impact through data science solutions.

At the same time, the role requires strong coordination skills — the ability to distribute work effectively within the team, support engineers, and ensure successful delivery together with the Engineering Manager.

Successful probation expectations:

During the probation period, we expect the successful delivery of a sports analytics or modeling product through:

• effective team orchestration,
• hands-on contribution to development,
• and high-quality execution of data science workflows.

Ideal candidate profile:

We would love to meet someone who is:

• proactive in communication and information gathering,
• focused on data-driven decision making,
• detail-oriented and demanding when it comes to production quality and best practices.

Also relevant:

• High-load real-time data environments, such as fintech, gaming, marketing analytics, computer vision, or similar domains, working with large-scale data streams.

We offer:

• Ability to work remotely
• Competitive and timely payment for services
• Flexible work schedule
• Personal mentoring and coaching
• Team building and corporate events
• 100% paid sick leave
• 20 working days of paid vacation
• Paid child care leave

Team Summary

Our analytical teams provide actionable insights during the development and rollout of AI-driven features, including motion and object detection. We quantify user experience for core device functionality, conduct deep-dive studies to shape the product roadmap, and evaluate new initiatives from initial trials through full-scale production.

Job summary

We are looking for an experienced Data Analyst/Engineer to join our team. In this role, you will develop self-service dashboards, build data models, monitor key product features, and collaborate with cross-functional teams to drive impactful decisions. This role offers an opportunity to work with large datasets, optimise analytical processes, and influence product growth with meaningful data insights.

Responsibilities and Duties

• Build data models for covering analytics
• Develop self-service dashboards for stakeholders
• Use data to analyse user behaviour, turning insights into practical guidance for product development and strategy
• Create reports that present data outcomes to stakeholders, enabling them to make informed decisions
• Use AI agents to automate routine tasks and ad-hocs

Qualifications and Skills

• 4+ years of experience as a BI/Data Analyst or Data Engineer
• Hands-on experience with data warehousing and ETL pipelines
• Advanced knowledge of SQL
• Hands-on experience with AWS (Athena, Redshift)
• Good written and spoken English

Nice to have

• Experience with AI agents
• Computer science fundamentals
• Knowledge of Python
• Hands-on experience with QuickSight, Tableau or PowerBI
• Good knowledge of statistics and probability theory

We offer multiple benefits that include

• The environment of equal opportunities, transparent and value-based corporate culture and an individual approach to each team member
• Competitive salary packages with performance-based annual reviews
• Opportunity to receive a Performance Bonus for your individual achievements and a Loyalty Bonus recognizing your dedication to the company
• Employment via Contract of Employment (UoP) in complete alignment with Polish Labour Law
• Guaranteed paid vacation, public holidays, and medical leaves as per statutory regulations
• Continuous growth and development opportunities through internal knowledge hubs, corporate courses, and free English classes
• Comprehensive private medical insurance to supplement your standard NFZ coverage

Domain: iGaming / Gambling
Format: Product company
Experience: 5+ years

About the Company

We are an international product company operating in the gambling sector. Our platform delivers real-time personalization for casino and sportsbook products using advanced machine learning. The solution processes live behavioral, transactional, and contextual data to improve player engagement, retention, and overall performance for operators worldwide.

Our focus is on building production-grade ML systems that directly influence what users see in real time — from game recommendations to personalized content and promotions.

Role Overview

We are looking for a Senior Data Scientist to join a product-focused team working on real-time personalization and recommendation systems for iGaming platforms.

This is a hands-on role that combines modeling, experimentation, and close collaboration with engineering and product teams in a high-load, real-time production environment.

Main Responsibilities

• Develop ML-driven features for casino products using supervised learning (regression, ranking, classification)
• Maintain and improve existing recommendation systems in production
• Enhance models using gradient boosting and other supervised approaches
• Perform data cleaning, preprocessing, and feature engineering
• Design and maintain pre- and post-processing workflows
• Optimize training and inference pipelines for performance and reliability
• Integrate ML models into Airflow pipelines in a multi-tenant environment
• Adapt and configure the solution for different clients (tenants)
• Collaborate closely with product and engineering teams on experimentation and feature delivery

As Part of the Team You Will

• Work cross-functionally with data scientists, engineers, product owners, designers, and researchers
• Analyze large-scale datasets to extract insights for product and business decisions
• Propose, implement, and evaluate ML approaches to solve real business problems
• Support and evolve a recommendation solution used across multiple tenants
• Influence product strategy through research, experimentation, and data-driven insights into user behavior

Experience & Education

• 5+ years of professional experience in data science
• Degree in a quantitative field (Mathematics, Statistics, Computer Science, or similar)

Core Skills

• Strong proficiency in Python and SQL
• Hands-on experience with data processing tools (Pandas, Polars)
• Solid engineering skills for building and maintaining scalable ML systems
• Experience implementing observability in ML pipelines (metrics, logging, alerting)
• Knowledge of Docker and Kubernetes
• Strong analytical mindset with the ability to solve loosely defined problems
• Hands-on experience with supervised ML techniques, including:
  • Regression and ranking models (XGBoost, LightGBM, CatBoost, neural networks)
  • Feature engineering and model evaluation (AUC, NDCG, MSE, uplift metrics)
  • Personalization or recommendation systems
• Proven experience deploying ML models to production (near real-time or batch)
• Solid understanding of statistical methods (A/B testing, significance testing)

Nice to Have

• Production experience with large-scale recommendation systems
• Experience with Airflow, Valkey/Redis, FastAPI in production
• Familiarity with contextual bandits or reinforcement learning
• Experience with AutoML tools

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.

Remote – Full-time – Flexible Hours - Shifted schedule to EST (New York) timezone

About TenViz

TenViz Predictive Analytics builds AI-powered solutions that help Fortune 100 investors anticipate market shifts before they become consensus. We combine financial expertise, mathematical rigor, and AI research to deliver predictive analytics for institutional investors.

Your Expertise

• Strong interest in quantitative and algorithmic approaches
• BSc/MSc in Math, Physics or related field with solid background in statistics, linear algebra and probability theory
• Advanced Linear Algebra, Advanced Statistics, Using Linear Algebra methods in Statistical analysis
• 2+ years in data research, quantitative modeling, ML prototyping, and backtesting
• Skilled in Python, SQL, Git
• Experience with  experiment tracking, pipeline orchestration and workflow automation

Nice to have:

• Bayesian inference, reinforcement learning, or ensemble methods
• Financial econometrics, time-series forecasting, or regime modeling

What You’ll Do

• Design predictive models using probabilistic, ML, and hybrid approaches
• Analyze large-scale financial datasets to detect hidden patterns and early regime shifts
• Prototype and evaluate algorithms, from deep learning to Bayesian models
• Write production-grade research code in Python/SQL that integrates into pipelines
• Translate results into insights and themes investors can act on — not just outputs

Example projects:

• Forecasting inflation via commodity price signals
• Constructing probabilistic forecasts of currency moves around macroeconomic announcements
• Designing a Bayesian model to estimate recession probabilities from yield curve dynamics
• Designing a regime-aware ML pipeline that switches models depending on market conditions
• Creating hybrid ensembles that outperform traditional benchmarks

What’s in It for You

• Remote-first, flexible hours
• Paid vacation & holidays (after 8 months)
• Continuous learning: advanced ML/DL workshops, probabilistic methods, optimization
• Supportive, collaborative team — no micromanagement, focus on trust and creativity
• Work on real financial problems where your models influence billion-dollar decisions

We are looking for a Middle Data Scientist (Computer Vision) to join our team and work on real-time intelligent systems operating in dynamic environments.

In this role, you will focus on developing and improving computer vision algorithms, working with image and video data, and building robust pipelines that perform reliably in real-world conditions. The position involves a mix of research and practical engineering, where you will experiment with different approaches, evaluate model performance, and contribute to the development of scalable, high-performance solutions.

This is a great opportunity for someone who enjoys solving complex problems, working with modern AI/ML technologies, and seeing their solutions applied in real systems.

THAT WOULD BE WONDERFUL IF YOU HAVE:

• 2+ years of experience in Computer Vision

• 2+ years of experience in Data Science / Machine Learning

• Strong Python skills

• Experience with any of the following: Google Cloud, AWS, Azure

• Hands-on experience with computer vision libraries

• Experience with deep learning frameworks (PyTorch or similar)

• Understanding of object tracking/detection approaches (classical + NN-based)

• Experience working with image/video data (preprocessing, dataset creation, augmentation)

• Solid understanding of model evaluation and benchmarking

• Hands-on experience with model optimization for edge deployment

• Understanding of real-time or near real-time systems

• Upper-intermediate english

WOULD BE A PLUS:

• Experience with C/C++ or Rust

• Experience with Linux-based systems

• Experience with SLAM

• Experience with robotics, control systems, or sensor-based systems

• Familiarity with edge devices (e.g., NVIDIA Jetson, Raspberry Pi)

• Experience with simulation environments

RESPONSIBILITIES:

• Research and implement image and video processing algorithms using both classical and deep learning approaches

• Benchmark and evaluate models across different scenarios and datasets

• Work with video data to create and refine datasets for training and validation

• Develop and improve processing pipelines for real-time performance

• Analyze system behavior in real-world and simulated scenarios to identify issues and improve performance

• Collaborate with engineering teams to integrate solutions into real-time systems

ADVANTAGES FOR A CANDIDATE:

• Stable and competitive salary;

• Legally compliant gig contract with official tax reporting and payment;

• Work in a cool & experienced team;

• Useful & exciting projects;

• Up to 26 Days Off per year at your convenience;

• Convenient office in Vinnytsia or an opportunity to work remotely;

• Corporate culture with maximum automation of processes;

• Review of working conditions and position based on performance, productivity and development in accordance with a skills assessment program

• Excellent opportunities and prospects for professional growth in a company with a 9-year history

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.

Who We Are

At Bennett Data Science, we've been pioneering the use of predictive analytics and data science for over a decade for some of the biggest brands and retailers. We're at the top of our field because we focus on delivering actionable AI for our clients. Our deep experience and product-first attitude set us apart from other groups and gets us the business results our clients want.

Why You Should Work With Us

You'll be exposed to a wide range of clients who are at the cutting edge of innovation in their field and get to work on fascinating problems, supporting real products, with real data. We help lots of companies, from some of the largest companies in the world to small startups in Silicon Valley who are building the next big thing.

Expert Mentorship: Direct guidance from senior staff with 20+ years of applied ML experience

Competitive Compensation: Market-rate pay with performance upside

Fully Remote: Work from any location of your choice, on a flexible schedule

Real Impact: Your models go into production and serve real users

The Role:

As a Senior Data Scientist, you will design, build, and deploy RAG systems and other AI solutions that help teams manage land, infrastructure, and stakeholder relationships more effectively. You'll work with large volumes of documents, permits, geospatial records, and stakeholder communications, turning unstructured and semi-structured data into reliable, queryable intelligence.

You'll own projects end-to-end: scoping the problem with internal and client-facing stakeholders, selecting retrieval and generation strategies, building and evaluating pipelines, and iterating on production systems alongside senior data engineers. You'll also contribute to the team's broader ML work: classification, extraction, geospatial modeling, and mentor junior team members as the practice grows.

This is a hands-on, senior individual contributor role. You'll need to be as comfortable explaining tradeoffs to a non-technical project manager as you are tuning a reranker or debugging retrieval recall. Client-facing communication is part of the job.

Requirements

A successful candidate has 5+ years of experience in applied data science and machine learning, with deep hands-on expertise in retrieval-augmented generation and a strong statistical foundation. They demonstrate the following:

RAG & Generative AI (Core Focus)

• Proven experience designing, building, and deploying RAG-based systems in production, including chunking strategies, embedding model selection, retrieval tuning, and reranking
• Strong understanding of hallucination mitigation techniques (grounding, citation enforcement, context window management, guardrails) and the ability to articulate tradeoffs across architectures
• Experience evaluating RAG pipeline quality end-to-end: retrieval recall, answer faithfulness, latency, and cost
• Familiarity with vector databases and hybrid search (e.g., Databricks, Pinecone, pgvector, or OpenSearch)

Applied ML & Engineering

• Production ML experience: building, deploying, and maintaining models that serve real users at scale
• Strong Python skills including scikit-learn, pandas, NumPy, and at least one deep learning framework (PyTorch or TensorFlow)
• Solid statistical foundation: hypothesis testing, distributions, probability, experimental design

Communication & Working Style

• Experience translating model behavior, recommendations, and limitations for non-technical stakeholders, particularly in domains where trust and accuracy are critical
• Comfort working independently across multiple projects simultaneously
• English proficiency at B2 or above (written and spoken)

Nice to Have

• Experience applying LLMs or transformer-based NLP for structured text classification, information extraction, or embedding-based retrieval
• Geospatial feature engineering, location-based statistics, spatial indexing, or proximity scoring, particularly in land, infrastructure, or utility corridor contexts
• Experience with Vision-Language Models (VLMs) or satellite/aerial imagery analysis for document or land parcel interpretation
• Experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI)
• Exposure to utilities, energy, infrastructure, land management, or enterprise SaaS domains
• Experience fine-tuning or adapting pre-trained models (LoRA, PEFT, or full fine-tune)
• Experience with agentic architectures and deployments

Position Overview

As a Game Mathematician, you will own the mathematical design of our gaming systems — from core probability models to long-term behavioral dynamics of the game.

You will shape RTP, volatility curves, hit frequency, payout distributions, risk balance, and overall economic sustainability of each title.

This role requires deep theoretical knowledge, practical simulation skills, and the ability to collaborate closely with producers, designers, engineers, and compliance teams.

Responsibilities

• Develop and maintain detailed mathematical models for Slots, Crash Games, and Fast Games.

• Design and balance RTP, volatility, hit frequency, paytables, game curves.

• Model stochastic processes and RNG logic, ensuring correctness and predictability.

• Calculate probabilities and payout distributions across long-run simulations.

• Conduct large-scale simulations and statistical analysis of game behavior.

• Balance risk, retention, and economic KPIs of the product.

• Collaborate with producers to create optimal player experience.

• Work closely with engineers to validate correct technical implementation.

• Contribute to game logic design and innovative mechanics.

• Conduct competitive analysis of game mathematics and market trends.

• Participate in playtests and analyze real in-game behavior post-launch.

• Prepare complete mathematical documentation for certification and regulators.

Requirements

• Strong knowledge of probability theory, combinatorics, and mathematical statistics.

• Experience in slot or gambling game mathematics (3+ years).

• Practical experience designing and balancing RTP, volatility, and payout structures.

• Experience with stochastic modeling and simulations.

• Programming skills (Python, R, C++, MATLAB, or similar).

• Ability to clearly communicate mathematical decisions to cross-functional teams.

• English — Intermediate or higher.

Would Be a Plus

• Experience with crash or fast game mechanics.

• Experience with competitive math research.

• Understanding of player behavior and retention impact.

• Experience interacting with certification bodies and regulators.

What We Offer

• Direct influence on product economics and player experience.

• Real ownership of game mathematics and long-term performance.

• Competitive compensation.

• Professional growth inside a product-driven gambling studio.

• Flexible working format.

• Strong, collaborative team environment.

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: 

• Design, implement, and optimize classical CV algorithms independently
• Develop and maintain components of SLAM/VIO pipelines
• Contribute to sensor fusion modules involving visual and inertial data
• Lead experiments, evaluate model performance, and propose improvements
• Review research papers and translate findings into practical solutions
• Collaborate across teams to ensure smooth integration of CV components.

Required Qualifications:

• Strong practical experience with classical CV and geometric vision
• Hands-on experience developing components of SLAM and/or VIO systems
• Proficiency in C++ and confident working in Linux environments
• Solid understanding of multi-sensor systems and data fusion
• Proven ability to prototype, benchmark, and optimize CV algorithms
• Ability to analyze research papers and implement state-of-the-art methods.

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

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

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv — you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

Join PwC Slovakia as a Junior AI Engineer, where you’ll have the opportunity to grow your skills and contribute to AI and data science solutions for leading global clients. This role is designed for developers and engineers who want to build, integrate, and deploy machine learning systems and data-driven applications. We are looking for candidates who enjoy coding in Python, working with data, and turning ideas into reliable, scalable solutions.

Project you could be involved in:

• Natural Language Data Exploration: Develop dashboards powered by AI for intuitive business data analysis.
• Document Interaction: Design tools enabling seamless interaction with unstructured and structured text documents.
• Knowledge Assistant: Implement ERP transformation with AI-powered tools to resolve employee inquiries efficiently.
• Agricultural Monitoring: Utilize Computer Vision for analyzing satellite imagery on a large scale.
• Automated Reconciliation: Create systems to identify anomalous transactions in accounting ledgers.

What You’ll Do:

• Project Participation: Participate in AI and data science projects from conception to deployment, contributing to solution design and supporting timely delivery of assigned tasks.
• Solution Development: Support the development of AI and ML solutions with a strong focus on Python-based implementation, working across areas such as Large Language Models (LLMs), RAG, classical machine learning and data analysis.
• Learning & Development: Continuously develop technical skills by following AI and data science trends, learning new approaches, and contributing to improvements of existing solutions and processes.

What We’re Looking For:

• Programming Skills (Key Requirement): Solid programming skills in Python (e.g. pandas, numpy, scikit-learn, plotly). Ability to write and understand code is essential. Experience with other programming languages is a plus.
• AI/ML Background: Hands‑on academic, project, or entry‑level experience with machine learning, data science, NLP, Computer Vision, or Generative AI (LLMs, RAG). The focus is on building or implementing solutions, not only using AI tools. Strong foundations in statistics and ML fundamentals are valued.
• Databases: Basic experience with SQL databases; familiarity with NoSQL databases is an advantage.
• Analytical Thinking: Strong analytical mindset with the ability to approach problems logically and creatively.
• Independence & Responsibility: Ability to work independently on assigned tasks and deliver results with guidance when needed.
• Language Skills: Fluent in English (B2 level or higher).

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

🌎 Akvelon is a USA-based software engineering and consulting company with offices across the USA, Poland, Serbia, Mexico, and Ukraine. We partner with global technology leaders and Fortune 500 companies to build enterprise platforms, AI/ML solutions, cloud systems, and large-scale digital products.

Project Description:

We are hiring a Senior Data Scientist for a fast-growing US product company operating in the digital identity, authentication, and fraud prevention space.

The platform processes billions of requests annually and serves enterprise customers across fintech, banking, healthcare, e-commerce, gaming, payments, and marketplace industries.

The team is focused on building production-grade AI/ML systems that improve trust, security, authentication flows, and customer experience at massive scale. This role involves close collaboration with ML 
Engineers and Engineering teams on experimentation, model monitoring, production analytics, and data-driven decision making.

You’ll work in a high-impact environment where machine learning systems directly influence product performance, fraud prevention strategies, and customer experience optimization.

Responsibilities:

• Develop, validate, and optimize machine learning and statistical models
• Design experiments and evaluate model performance using rigorous statistical methods
• Collaborate with ML Engineers on deployment pipelines and production workflows
• Monitor deployed models for drift, reliability, and performance degradation
• Build dashboards and monitoring systems for ML observability
• Provide actionable business recommendations based on model performance
• Work with raw datasets and optimize data workflows together with Data Engineering teams
• Communicate findings to both technical and non-technical stakeholders
• Mentor team members and contribute to best practices for production ML systems

Requirements:

Must-have:

• 5+ years of commercial experience in Data Science / Applied ML
• Strong Python expertise (pandas, scikit-learn)
• Strong background in statistical modeling and experimentation
• Advanced SQL skills and experience with Snowflake
• Experience working with production ML systems
• Experience monitoring deployed ML models (drift, retraining, performance analysis)
• Proficiency with cloud platforms (AWS)
• Experience collaborating with ML Engineers and cross-functional teams
• Strong communication and stakeholder management skills
• Upper-Intermediate+ English
• Master’s or PhD in Statistics, Computer Science, Data Science, or related field
• (or equivalent experience).

Nice-to-have:

• PyTorch or TensorFlow
• GenAI / AI observability / telemetry systems
• Looker or similar BI/dashboarding tools
• API and deployment workflow knowledge
• Experience mentoring engineers or data scientists
• R, Java, or Go exposure

Working Conditions & Benefits:

• Paid vacation and sick leave
• Overlap with PST timezone through 10 AM PST
• Official state holidays — 9-11 public holidays per year
• Professional growth through challenging projects and the opportunity to master new technologies
• Flexible working schedule: 8 hours per day, 40 hours per week
• Personal Career Development Plan (CDP)
• Employee support programs (discounts, healthcare, legal assistance)
• Paid external training, conferences, and professional certifications aligned with business goals
• Internal workshops, seminars, and English classes
• Corporate library with paper and e-books

This position is not open to U.S.-based applicants.
 

Ready to work on production-grade AI systems with real business impact? Apply now and join our team.

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.