Jobs Data Science

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

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 Scientist/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.

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.

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.

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 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 🚀

We are seeking a highly specialized Data Scientist / Analytics Consultant to support a project focused on revamping real estate data stack and pricing accuracy.

About Project:

Our client specializes in delivering real-time Investor Pricing Ranges to agents and investors using a combination of AVMs, third-party data providers, and internal logic. As the platform scales, ensuring data quality, consistency, and pricing accuracy is critical to marketplace trust, conversion, and transaction volume.

What will you do?
—Conduct a comprehensive audit of existing real estate data providers and infrastructure;
—Benchmark and validate the performance of various AVMs and property data feeds;
—Analyze current underwriting and valuation models, identifying gaps, biases, or inefficiencies in pricing logic;

—Refine renovation assumptions and their impact on final pricing outputs;

—Deliver a clear, actionable roadmap and hands-on adjustments to improve the reliability of  Investor Pricing Range;

—Collaborate closely with  internal product and engineering teams to ensure swift implementation of your recommendations.

What do we expect?
—High proficiency in Python (Pandas, NumPy, Scikit-learn);

—Hands-on experience integrating and evaluating standard real estate APIs and data providers (e.g., MLS feeds, ATTOM, CoreLogic, HouseCanary, SmartZip, or similar);

—Experience working with spatial data and GIS tools (e.g., PostGIS, GeoPandas, H3);

—Deep understanding of real estate investment metrics, including ARV (After Repair Value), Cap Rates, Yield;

—Proven track record of building, tuning, or auditing predictive pricing models (e.g., XGBoost, LightGBM, CatBoost, Random Forest, or other ensemble methods applied to real estate);

—Ability to build clear dashboards (Tableau, Looker, PowerBI, etc.);
—At least Upper-Intermediate English level (speaking & writing).

Application Process:
—Initial screening: call with Recruiter;
—Tech interview;
—Сlient’s interview.

If you're ready to bring your expertise, we’d love to meet you!

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.

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.

🚀 Who we are
Adaptiq is a technology hub helping fast-growing product companies build and scale high-performing R&D teams. We partner with innovative startups and established tech businesses to deliver cutting-edge solutions across industries.
 

🧠 About the Product
Our platform is a cloud-based AI-driven workspace that automates statistical analysis validation and generation for clinical research. It serves large pharmaceutical and biotech clients by extracting, validating, and producing complex tabular outputs and regulatory deliverables. 

The system handles high volumes of hierarchical tables, figures and listings, applying both classical and generative NLP to accelerate review cycles, reduce manual double-programming and maintain a full audit trail. 
 

🎯 Your Role
We are looking for a Strong Data Scientist with a focus on NLP and Generative AI to drive the development of intelligent systems that automate complex analytical workflows.

This is a research-driven role, where you will take ownership of problems end-to-end — from understanding the data, to experimenting with approaches and delivering solutions that can be integrated into production.

🔧 What you’ll do

• Define and drive the AI research roadmap, mentoring peers on practical implementation.
• Design, develop and evaluate NLP and tabular-data algorithms using GenAI, retrieval-augmented generation (RAG), deep learning, classical ML, NER and rule-based methods.
• Explore large clinical datasets, perform data cleaning and feature engineering for downstream model training.
• Build and maintain data pipelines for extraction, transformation and preprocessing of structured and semi-structured inputs.
• Stay current on state-of-the-art techniques in NLP, generative AI and tabular-data analysis, and integrate best practices.
• Collaborate with cross-functional teams, including software developers, DevOps engineers to integrate the research solutions into production. 
   

✅ What we’re looking for

• 3–5 years of industry experience with NLP as a core focus
• Experience working with structured or tabular data combined with NLP
• 2+ years of hands-on experience with deep learning methods and frameworks (e.g. PyTorch, TensorFlow).
• Strong hands-on experience with Generative AI / LLM-based systems (e.g. RAG, structured output generation, text-to-SQL)
• Solid understanding of classical NLP techniques (NER, parsing, rule-based methods)
• Proven ability to build and experiment with different approaches, not just implement predefined solutions
• Experience delivering AI solutions in real-world / production environments
• Strong Python skills for data analysis, experimentation, and prototyping
• MSc or PhD in CS, ML, Data Science, or related field
• Strong English communication skills

⭐️ Nice to have

• Familiarity with cloud-based NLP platforms and MLOps tooling.
• Experience with large-scale table analytics or regulatory statistical outputs.

🎁 What we offer

• 20 working days of paid vacation + public holidays
• Full accounting & legal support
• Fully remote setup + co-working option
• High-performance equipment
• Competitive compensation with regular performance reviews

💡 Why this role is interesting

• Work at the intersection of NLP, GenAI, and real-world healthcare impact
• Solve non-trivial data problems (tables + text + regulations)
• Influence a live product used by global pharma companies
• Strong focus on research + practical implementation

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

Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

About the Product:

Our platform is a cloud-based AI-driven workspace that automates statistical analysis validation and generation for clinical research. It serves large pharmaceutical and biotech clients by extracting, validating, and producing complex tabular outputs and regulatory deliverables. 

The system handles high volumes of hierarchical tables, figures and listings, applying both classical and generative NLP to accelerate review cycles, reduce manual double-programming and maintain a full audit trail. 

About the Role:

We are looking for a Strong Data Scientist with a focus on NLP and Generative AI to drive the development of intelligent systems that automate complex analytical workflows.

This is a research-driven role, where you will take ownership of problems end-to-end - from understanding the data, to experimenting with approaches and delivering solutions that can be integrated into production.

Key Responsibilities:

• Define and drive the AI research roadmap, mentoring peers on practical implementation.
• Design, develop and evaluate NLP and tabular-data algorithms using GenAI, retrieval-augmented generation (RAG), deep learning, classical ML, NER and rule-based methods.
• Explore large clinical datasets, perform data cleaning and feature engineering for downstream model training.
• Build and maintain data pipelines for extraction, transformation and preprocessing of structured and semi-structured inputs.
• Stay current on state-of-the-art techniques in NLP, generative AI and tabular-data analysis, and integrate best practices.
• Collaborate with cross-functional teams, including software developers, DevOps engineers to integrate the research solutions into production. 

Required Competence and Skills:

• 3–5 years of industry experience with NLP as a core focus
• Experience working with structured or tabular data combined with NLP
• 2+ years of hands-on experience with deep learning methods and frameworks (e.g. PyTorch, TensorFlow).
• Strong hands-on experience with Generative AI / LLM-based systems (e.g. RAG, structured output generation, text-to-SQL)
• Solid understanding of classical NLP techniques (NER, parsing, rule-based methods)
• Proven ability to build and experiment with different approaches, not just implement predefined solutions
• Experience delivering AI solutions in real-world / production environments
• Strong Python skills for data analysis, experimentation, and prototyping
• M.S. or Ph.D. in Computer Science, Machine Learning or a related quantitative field.
• Excellent collaboration, interpersonal skills and ability to work independently with minimal oversight.
• Strong written and verbal communication in English.

Nice to Have:

• Familiarity with cloud-based NLP platforms and MLOps tooling.
• Experience with large-scale table analytics or regulatory statistical outputs.

We’re looking for a Senior Data Scientist to join a fast-growing R&D team working with large-scale, real-time data in the AdTech domain.

This is not a pure research role — we need someone who can take ownership end-to-end: from idea → modeling → production.

About the Role

You’ll work on high-load systems processing billions of requests, building data-driven solutions that directly impact large-scale digital products and decision-making.

Responsibilities

• Analyze large-scale, complex datasets to uncover insights and opportunities
• Design and build scalable data pipelines
• Develop and deploy ML models (classification, regression, recommendation systems)
• Work with real-time (online) data processing systems
• Improve existing data products and create new ones
• Collaborate with Product, BI, Engineering, DevOps, and Marketing teams
• Own the full lifecycle: research → implementation → production → monitoring

Requirements (Must-have)

• 4+ years of experience as a Data Scientist (6+ preferred)
• Proven experience in AdTech / programmatic advertising
• Hands-on experience with high-load systems (billions of requests)
• Experience working in real-time environments
• Strong background in Machine Learning (tree-based models, recommendation systems)
• Solid Python skills with ML libraries (e.g., XGBoost, LightGBM)
• Strong SQL and data querying skills
• Experience with monitoring tools (e.g., Grafana, Kibana)
• Ability to work end-to-end (research → production)
• English level: C1 (Advanced) with strong communication skills

Nice to Have

• Deep understanding of AdTech ecosystem (DSPs, SSPs, Ad Exchanges)
• Experience with databases like Vertica, VoltDB, MongoDB
• Familiarity with PMML                                                                        Hiring Process
• Technical interview
• Home assignment
• HR interview

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 us as a Data Architect / Lead and play a key role in shaping the data foundation behind our next generation of analytics and AI solutions. In this position, you’ll define the architecture vision for our modern data ecosystem, guide a growing team of Data Engineers, and build cloud‑native platforms that unlock enterprise‑wide insights. This is a high‑impact role where you’ll work closely with business and technology leaders, influence strategic decisions, and drive the adoption of advanced analytics and Generative AI across the organization.

What You’ll Do:

Lead & Strategize

• Lead and mentor Data Engineers, fostering innovation and continuous improvement.
• Own the data architecture vision aligned with business goals.
• Partner with executives and stakeholders to turn strategic needs into scalable data solutions.

Architect & Build

• Design and optimize modern data platforms using Azure Data Lake, Databricks, SQL Server, Microsoft Fabric, and NoSQL.
• Build robust, scalable data pipelines across diverse data sources.
• Implement strong data quality, governance, and security practices.
• Support advanced analytics, machine learning, and AI-based solutions.

Enable Insights

• Build solutions that deliver accurate, timely insights for decision-makers.
• Collaborate on Power BI dashboards and executive reporting.
• Integrate Generative AI into insight-generation workflows.

Requirements:

• Bachelor’s degree in Computer Science, Data Engineering, or related field.
• 4+ years in data engineering, architecture, or analytics roles.
• Experience leading Data Engineering teams in enterprise settings will be a plus.
• Strong skills in Azure data services, Databricks, SQL, NoSQL, and Microsoft Fabric.
• Hands-on Power BI and enterprise reporting experience.
• Proven ability to build data pipelines and enforce data quality.
• Excellent communication skills, especially with executive stakeholders.
• Relevant certifications (Azure Data Engineer, Databricks, Fabric Analytics, etc.) are a plus.

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

Project

The project focuses on a deep refactoring and optimization of the reporting ecosystem combining Salesforce CRM and Tableau. The main goal is to redesign current data flows, replacing the bulky and slow architecture with a modular system of reusable components. You will work on a process redesign to ensure speed, data accuracy, and ease of future system maintenance.

Responsibilities

• Development and Redesign: designing and supporting complex interactive visualizations in Tableau Desktop with a focus on modularity.
• Architecture Optimization: transforming bulky data flows into a fast and stable reporting system.
• Integration and Setup: working with data streams from Salesforce CRM and ERP systems (SAP, Odoo, MS Business Central).
• Technical Optimization: performance tuning (Data Extracts, calculated fields, SQL query optimization).
• Business Collaboration: gathering requirements from stakeholders and translating them into clear technical specifications for visualization.
• Data Governance: ensuring data accuracy, integrity, and security (including Row-Level Security).

Requirements

• Must-have:
  • 1.5-2+ years of commercial experience with Tableau (Desktop, Server/Cloud) or other BI tools.
  • Strong SQL skills (writing complex queries, joins, CTEs).
  • Understanding of CRM and ERP system architecture (how data is stored and interconnected).
  • Intermediate+ English level (for technical communication and documentation).
• Nice-to-have:
  • Experience with Tableau and Salesforce integration (a significant plus).
  • Experience with Tableau Prep or other ETL tools (Alteryx, KNIME).
  • Tableau Desktop Specialist or Certified Data Analyst certification.
  • Experience with cloud data warehouses (Snowflake, BigQuery, AWS Redshift).

Conditions

• Collaboration Type: Part-time (Freelancer / Contract).
• Location: Remote.
• Schedule: Flexible (details to be discussed based on your availability).

Selection Process

1. Recruiter screening.
2. Technical interview with the Tech Lead.
3. Offer.