Jobs Data Scientist

MINT is the leader in Advertising Resource Management (ARM) software, driving marketing transformation in the age of agentic AI. At the core of our innovation is an open enterprise platform that deploys autonomous AI agents to augment human teams across the marketing and advertising value chain, connecting marketing performance with enterprise growth and real business impact.

Thanks to a diverse team of over 300 professionals worldwide, we integrate technology, data, and agentic intelligence to redefine how global brands and agencies plan, execute, and optimize their advertising investments.

With the recent acquisitions of technology leaders Redmill Solutions and info³, MINT has further expanded its unified ecosystem, completing the long-awaited connection of media planning, buying, and execution within one intelligent environment.

The Role

We are looking for a Senior Data Architect — a strategic, hands-on, and forward-thinking leader passionate about reshaping complex data ecosystems, who will drive the transformation of our ARM platform by unifying multi-tenant data models, enabling scalability at growing volumes, and designing a foundation for future modules such as Financial Operations and Compliance.

This is a consultancy engagement, not an employment contract. The selected consultant will work independently, bringing their specialized knowledge and experience to our projects.

What you'll be doing:

Target Architecture Definition

• Conduct a comprehensive audit of the existing data landscape
• Assess current data models, data flows, and technical gaps (scalability, consistency, traceability)
• Evaluate build vs. refactor vs. reuse strategies for ARM 2.0
• Define target architecture principles aligned with product and business goals

Unified Data Modelling

• Design a shared, scalable multi-tenant data model
• Enable deep client configurability without fragmenting the core schema

Orchestration Architecture

• Architect APIs, event-driven systems, and caching layers
• Design end-to-end data flows (inbound and outbound) across multiple data sources and media platforms
• Ensure full traceability of media investments across the value chain (planning → buying → finance → reconciliation)
• Guarantee performance, consistency, and seamless integrations (e.g., SAP/ERP, third-party media tools)

AI/ML Foundations

• Prepare the platform for advanced analytics and AI-driven capabilities
• Support use cases such as: Media data quality scoring, anomaly detection, allocation recommendations, incentives management

This role will be a great fit if: 

• You are a seasoned data professional with 8–12 years of experience in engineering and analytics, including at least 4 years specifically dedicated to high-level data architecture. 
•  You have a proven track record of designing multi-tenant B2B SaaS platforms and navigating complex ecosystems with intricate third-party integrations, such as ERPs or media platforms (experience in AdTech is a definite advantage).  
• Your expertise in data modeling is comprehensive, spanning conceptual, logical, and physical layers, with a unique ability to design highly configurable systems while maintaining absolute data integrity.  
• You are a master of the trade-offs between normalization, performance, and maintainability, and you bring deep knowledge of Master Data Management (MDM) to the table.  
• Technically, you are hands-on with AWS and Snowflake, possessing the skills to architect massive event-driven and API-led data pipelines.  
• Ideally, your expertise is backed by an AWS Solutions Architect (Professional) or Data Engineer certification, reflecting your ability to build scalable, world-class infrastructure. 

Interview Process

Candidates can expect the following steps in our interview process:

• HR Video Interview (30 minutes): A virtual interview with HR to provide an overview of the company and the role, as well as to gain insight into your experience and background.
• Technical Interview with Tech team (1 hour): A virtual interview with the VP Engineering or other Team members, focused on your technical expertise, past experience, and problem-solving approach.
• Final Interview with the CPTO (30 min)
• Offer: after completing the interview process, successful candidates will receive an offer.

MINT is committed to a diverse and inclusive workplace. MINT AI is an equal opportunity employer and does not discriminate on the basis of age, race, religion, color, national origin, gender, gender identity, gender expression, sexual orientation, immigration status, medical condition, protected veteran status, disability, genetic information, political views or activity, or other legally protected status.

Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the client: The company is a trailblazer in the world of data-driven advertising, known for its innovative approach to optimizing ad placements and campaign effectiveness through advanced analytics and machine learning techniques. Its mission is to revolutionize the advertising sector by enabling brands to reach their audiences more effectively.

About the role: The company is seeking an experienced Senior Data Scientist to join its dynamic team. The role requires expertise in supervised learning, reinforcement learning, and optimization techniques, and involves developing advanced machine learning models, generating actionable insights, and optimizing advertising solutions.

Responsibilities:
- Develop and implement advanced supervised and reinforcement learning models to improve ad targeting and campaign performance.
- Collaborate with cross-functional teams to identify opportunities for leveraging machine learning and optimization techniques to solve business problems.
- Conduct extensive data analysis and feature engineering to prepare datasets for machine learning tasks.
- Apply optimization algorithms to enhance the effectiveness and efficiency of advertising campaigns.
- Evaluate and refine existing models to enhance their accuracy, efficiency, and scalability.
- Utilize statistical techniques and machine learning algorithms to analyze large and complex datasets.
- Communicate findings and recommendations effectively to both technical and non-technical stakeholders.
- Work with engineering teams to integrate models into production systems.
- Monitor, troubleshoot, and improve the performance of deployed models.
- Mentor junior data scientists and contribute to the continuous improvement of the data science practice within the company.

Requirements:
- 5+ years of experience in data science or machine learning roles, with a strong focus on supervised learning, reinforcement learning, and optimization techniques.
- Proficiency in Python.
- Strong understanding of working with relational databases and SQL.
- Experience with machine learning libraries such as scikit-learn, TensorFlow, PyTorch, or similar.
- Deep understanding of statistical modeling and supervised learning algorithms (e.g., linear regression, logistic regression, decision trees, random forests, SVMs, gradient boosting, neural networks).
- Experience with reinforcement learning algorithms and frameworks like OpenAI Gym.
- Experience with optimization algorithms (linear, non-linear, combinatorial, etc.).
- Experience with data manipulation tools and libraries (e.g., pandas, NumPy).
- Familiarity with cloud services, specifically AWS, is a plus.
- Experience building and managing cloud-based ML pipelines using AWS services (e.g. SageMaker, Bedrock) is a plus.

Other Skills:
- Strong analytical and problem-solving skills.
- Excellent communication skills, with the ability to clearly articulate complex concepts to diverse audiences.
- Ability to work in a fast-paced environment and manage multiple priorities.
- Strong organizational skills and attention to detail.
- Ability to mentor and guide junior data scientists.
- Must be able to communicate with U.S based teams

The company offers:
- An opportunity to be at the forefront of advertising technology, impacting major marketing decisions.
- A collaborative, innovative environment where your contributions make a difference.
- The chance to work with a passionate team of data scientists, engineers, product managers, and designers.
- A culture that values learning, growth, and the pursuit of excellence.

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:
- remote time job, B2B contract
- 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
 

We are looking for the first Data Science engineers to join our team and play a foundational role in building a private Large Language Model from the ground up. This is a rare opportunity to shape the technical direction, influence architectural decisions, and establish best practices for intelligent systems within the organization.

What you will do: 

• Design, build, and maintain classical machine learning models to support core product needs.
• Develop agent-based systems (LLM agents, multi-step agents, agent-to-agent workflows) as part of the broader LLM ecosystem.
• Conduct rigorous experiments and iterate quickly to validate approaches and improve system performance.
• Build and optimize inference pipelines, including performance tuning, monitoring, and alerting.
• Collaborate closely with Data Engineering to deploy models securely and reliably into production environments.

• Contribute to defining standards, workflows, and tooling for the new Data Science function.

   

What we expect:

• 3+ years of hands-on experience with Python.
• Strong SQL skills and understanding of data workflows.
• Solid grasp of machine learning methods and their practical applications.
• Experience building agents or agent-based systems is a strong plus.
• Initiative, ownership, and readiness to work in a greenfield environment where many solutions must be defined from scratch.

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.

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:

As a Strong Data Scientist you will own the end-to-end development of novel AI and algorithmic solutions that power our core platform. You will translate research hypotheses into proofs of concept, select and benchmark advanced NLP and tabular-data techniques, and collaborate with engineering teams to integrate your work 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 in NLP and/or tabular-data processing within a production setting.
• 2+ years of hands-on experience with deep learning methods and frameworks (e.g., PyTorch, TensorFlow).
• Expertise in both classical NLP (tokenization, NER, parsing, rule-based) and generative NLP (text-to-SQL, table generation, RAG).
• Advanced Python programming skills and familiarity with data science libraries (pandas, scikit-learn).
• Proven track record of delivering AI-driven projects into production environments.
• M.S. or Ph.D. in Computer Science, Machine Learning or a related quantitative field.
• Strong written and verbal communication in English.
• Excellent collaboration, interpersonal skills and ability to work independently with minimal oversight.

Nice to Have:

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

Why Us:

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

We offer a highly competitive package with yearly performance and compensation reviews.

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. 

About project: Mobile marketing and audience platform

Project: sell-side omnichannel advertising platform powered by real-time mobile audiences. We deliver hundreds of millions of ads per day across thousands of global leading apps and websites. Our platform uses AI to deliver more efficient, effective and precise digital advertising campaigns. Our direct integration with thousands of mobile publishers gives us access to more than 50 billion first-party data signals per day across the globe. Marketers use these anonymized signals to understand and predict consumer behavior, identify new opportunities and fuel business growth.
 

Role Overview:

If you’re a talented Data Scientist looking to be part of a fast-growing, innovative R&D team, shape the future of decision-making in business, work on cutting-edge technologies and vast amounts of global real-time data, affect billions of mobile users, and become an industry leader - then let’s talk!

Our mobile data platform enables organizations to uncover insights and make data-driven decisions that enhance strategies and drive growth. We are seeking a Senior Data Scientist to join our Data Science & Engineering team.
 

Responsibilities:

• Analyze large and complex data to discover hidden patterns and opportunities.
• Develop and own end-to-end highly scalable data pipelines.
• Develop state-of-the-art machine learning models, and algorithms and build solutions in monetization fields.
• Provisioning data models for real-time (online) processing
• Shape new data products, and constantly improve the existing products.
• Collaborate with multiple teams including Product, BI, Analysts, DevOps, R&D and Marketing to lead and accomplish overall solutions.
• Oversee a complete release to production, including analyzing requirements, testing, monitoring and measuring results, multitasking, and quickly responding to critical issues.

Requirements:

Must:

• B.Sc./M.A/M.Sc. degree in Computer Science, Engineering, Math, Statistics, or other equivalent fields.
• 6 years as a Data Scientist - a strong background in ML concepts and models.
• Hands-on experience with Python, especially with data science ML libraries (regression & classification algorithms e.g. XGB or LGBM, recommendation system algorithms, etc.)
• Understanding of databases and SQL for data retrieval.
• Monitoring and alerting tools (e.g. Grafana, Kibana)
   

Advantage:

• Knowledge in the programmatic advertising landscape – DSPs, SSPs, exchanges – significant advantage.
• Experience with relational (e.g. Vertica, VoltDB) and non-relational (e.g. MongoDB) databases.
• Experience with PMML
  
  Interview process: 2-3 stages (technical/test task and interpersonal + HR).

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

Project overview

The project focuses on building a governed conversational BI solution on Databricks using Genie. It includes designing scalable data architecture, implementing strong data governance with Unity Catalog, and enabling reliable SQL and AI-driven data consumption through well-defined semantic models.

Responsibilities

• Define and oversee the governed conversational BI architecture on Databricks using Genie
• Ensure governance from day zero, including compliance with Unity Catalog policies for all data assets
• Implement RBAC, row-level security (RLS), lineage, and audit logging
• Design and validate the Medallion architecture (Bronze / Silver / Gold layers)
• Define CI/CD processes in Azure Pipelines for semantic model management
• Oversee the setup of two Genie Spaces and ensure guardrail responses for out-of-scope questions
• Drive quality gates, benchmark cycles, and SME validation processes
• Build and maintain semantic models and knowledge structures
• Define data models for SQL and AI consumption

Requirements

• Experience with Databricks (on Azure), including Lakeflow pipelines
• Strong knowledge of Unity Catalog, including data governance, RBAC, and lineage
• Experience working with Genie (Databricks AI-powered analytics interface)
• Experience with CI/CD processes using Azure Pipelines for semantic model version control
• Strong SQL experience, including SQL Warehouse, Delta Lake, and Gold schema management
• Knowledge of PII masking, encryption, and audit/compliance frameworks
• Experience with template-based deterministic SQL design

🚀 Senior Data Scientist / Forecasting (AWS)

We’re looking for a Senior Data Scientist with deep expertise in time-series forecasting and AWS, to lead the design and delivery of large-scale, end-to-end forecasting systems that directly impact business decisions.

This role is perfect for someone who thrives at the intersection of advanced modeling, experimentation, and real-world business impact.

🌍 About the Role

You will own the full forecasting lifecycle across SKU, store, channel, and time hierarchies, shaping how data drives key decisions such as demand planning, inventory optimization, and allocation.

This is a high-impact, strategic role where you will define modeling approaches, drive experimentation, and influence both product and operational outcomes.

🧩 Key Responsibilities

• Lead the development of end-to-end forecasting systems across complex business dimensions
• Define modeling strategies and evaluation frameworks aligned with real business use cases
• Design and own experimentation frameworks (A/B testing, causal inference, counterfactual analysis)
• Quantify the business impact of forecasts (service levels, inventory, cost, planner decisions)
• Set the technical direction for modern forecasting approaches, combining:
  • statistical models
  • machine learning & deep learning
  • LLM-enabled techniques (embeddings, hybrid architectures)
• Apply advanced time-series methodologies, including:
  • hierarchical forecasting
  • intermittent demand
  • demand sensing
  • Forecast Value Added (FVA)
• Own production deployment and lifecycle:
  • cloud-native architectures (AWS)
  • scalable pipelines and APIs
  • monitoring, retraining, and MLOps practices
• Collaborate with product, engineering, and operations teams to turn ambiguous problems into clear, actionable solutions

🛠️ Tech Stack & Requirements

• Strong experience with AWS (must-have)
• Deep expertise in time-series forecasting (must-have)
• Experience with:
  • Python, ML/DL frameworks
  • large-scale data pipelines
  • MLOps and production systems
• Solid background in statistics, experimentation, and causal inference

💡 Why Join

• Work on high-impact forecasting problems that directly influence business decisions
• Own end-to-end solutions — from modeling to production
• Shape the future of data-driven planning and optimization
• Collaborate with senior stakeholders across product, engineering, and operations

Data Scientist - Senior - Computer vision
 

About Cyberette
Cyberette is an AI-native cybersecurity company developing forensic-grade technology to detect digital manipulation across video, audio, and images. Our mission is to restore trust in digital communication and protect people, organizations, and institutions from deception in the AI era.

About the Role
We are looking for a Computer Vision Data Scientist with strong initiative and technical excellence to join our core development team. You’ll be responsible for designing, training, and optimizing computer vision models and architectures used in our deepfake detection and forensic analysis platform.

This role requires someone who thrives in fast-paced environments, loves solving complex problems, and brings both creativity and rigor to their work. You’ll collaborate closely with our founders and engineers to push the limits of multimodal AI for real-world impact.

Key Responsibilities

• Develop, train, and deploy computer vision models for image and video manipulation detection.
• Research and experiment with new architectures, model ensembles, and multimodal fusion techniques.
• Preprocess, clean, and manage large-scale datasets for training and evaluation.
• Optimize model accuracy, latency, and scalability for enterprise-grade performance.
• Contribute to the design of the model evaluation framework and internal benchmarking tools.
• Collaborate with other engineers and researchers to integrate models into production pipelines.
• Document methodologies, experiments, and findings clearly and systematically.

Requirements

• MSc/PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field.
• Strong experience in computer vision (CNNs, Transformers, multimodal models).
• Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).
• Solid understanding of ML ops, dataset curation, and model evaluation.
• Proven experience building and training models from scratch.
• Excellent analytical and problem-solving skills.
• Self-driven, disciplined, and collaborative mindset.

What We Value
At Cyberette, we believe technology should serve people. We are a team of builders united by a shared sense of purpose — creating tools that make the digital world safer and more truthful. If you care deeply about impactful innovation and want your work to matter, you’ll feel at home here.

Bonus Skills

• Experience with audio or multimodal analysis.
• Knowledge of adversarial attacks or deepfake generation methods.
• Experience in real-time inference or edge deployment.

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 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
You’ll be working on a cloud-based AI platform transforming clinical research workflows.

The system automates validation and generation of statistical analyses for large pharmaceutical and biotech companies — reducing manual work and accelerating delivery of regulatory outputs.

At its core, the platform:

• Processes complex hierarchical tables, figures, and listings
• Combines classical NLP + Generative AI
• Ensures full traceability and auditability (critical for clinical environments)
   

🎯 Your Role
As a Data Scientist, you’ll work on NLP and tabular data challenges, taking ideas from hypothesis to prototype and influencing real product decisions.

This is a hands-on, research-driven role with real production impact.

🔧 What you’ll do

• Build and prototype NLP solutions (NER, classification, parsing, GenAI)
• Work with LLMs and RAG pipelines for structured outputs
• Design and implement tabular data processing pipelines
• Explore and analyze complex clinical datasets
• Compare approaches, run experiments, and optimize model performance
• Contribute to production-ready AI systems
• Write clean, reproducible, well-documented code
   

✅ What we’re looking for

• 2–4 years of experience in Data Science with strong NLP focus
• Hands-on experience with Generative AI / LLMs (RAG, structured outputs, etc.)
• Experience with tabular + text data combined
• Solid knowledge of classical NLP (NER, parsing, rule-based methods)
• 1+ year with deep learning frameworks (PyTorch, TensorFlow)
• Strong Python skills for experimentation and prototyping
• Experience evaluating models and selecting best-performing approaches
• Exposure to production AI systems
• MSc or PhD in CS, ML, Data Science, or related field
• Good English communication skills

⭐️ Nice to have

• Experience with cloud AI/NLP platforms or managed services

🎁 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

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:

As a Middle Data Scientist, you will support the development of novel AI and algorithmic approaches—particularly in NLP and tabular data—to enhance our core platform. You will take hypotheses through proof-of-concept, explore complex clinical datasets, identify patterns, evaluate alternative methods, and recommend optimal solutions. 

Key Responsibilities:

• Design, develop, and prototype NLP algorithms (classical and generative) for document parsing, NER, classification, and table generation

• Implement tabular data models and pipelines for metadata extraction, transformation, and validation

• Work with large, heterogeneous clinical datasets: clean, preprocess, and structure data for analysis

• Evaluate multiple algorithmic approaches, benchmark performance, and select optimal solutions

• Maintain reproducible code, thorough documentation, and version control for research assets

Required Competence and Skills:

• 2- 4 years of industry experience in NLP and/or tabular data processing
• 1+ years of hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow)
• Proven track record of delivering AI-driven projects into production
• Expertise in classical NLP techniques and generative methods (e.g., text-to-SQL, generative tabular models)
• Strong proficiency in Python and associated data science libraries
• M.S. or Ph.D. in Computer Science, Data Science, Statistics, or related quantitative field
• Excellent English communication skills, both written and verbal

Nice to Have:

• Experience with cloud-based NLP platforms or managed AI services

Why Us:

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

We offer a highly competitive package with yearly performance and compensation reviews.