Jobs Data Science

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

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

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

💼 About Atto Trading — Where Engineering Meets Finance

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

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

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

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

🧠 During the internship, you will do:

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

📌 Program Details

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

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

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

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

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

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

Our values:

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

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

Responsibilities:
 

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

Requirements:
 

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

Would be a plus:
 

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

Personal qualities:
 

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

Mastery of the following technologies/tools the team uses:

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

Employee Benefits:

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

🚀 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

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

Requirements:

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

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

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

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

- Strong problem-solving, leadership, and communication skills

Nice to have:

- Experience leading ML projects end-to-end

- Background with big data technologies (Spark, Hadoop)

- Experience with ethical AI and bias mitigation

Location: Malmö, Sweden

Company offers:

- Long-term employment with possibilities for professional growth

- Fully remote work

- Reasonably flexible schedule

- 15 days of paid vacation

- Regular performance reviews

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.

Evowill is looking for a Data Science Mentor to join our team. If you’re excited to share your knowledge with beginners in data science and machine learning, and enjoy teaching or want to try yourself in this role, we would be happy to collaborate!

You are:

• A Data Scientist/Data Analyst with 3–5+ years of experience in Data Science, Machine Learning, or Data Analytics;
• Patient, responsible, and well-organized;
• Interested in teaching and knowledge sharing;
• Curious and eager to learn, just as much as to teach;
• Proficient in writing clean, readable, and reproducible code;
• Passionate about helping others grow technically and intellectually;

• Comfortable working remotely with a flexible schedule (Ukrainian timezone).

   

We are:

• A Ukrainian-Colombian team;
• Working with Python, Data Science, and AI-related projects;
• Supported by experienced mentors who will help you onboard;

• Focused on growth, learning, and continuous improvement.

   

Technical skills:

• Strong proficiency in Python for data analysis;
• Hands-on experience with NumPy, Pandas, and Scikit-learn;
• Experience with both structured and unstructured data
• Solid understanding of machine learning concepts (classification, regression, clustering);
• Knowledge of statistics, basic and modern modeling techniques;
• Experience with Jupyter Notebooks or similar tools;
• Data handling skills: cleaning, preprocessing, and visualization (Matplotlib, Seaborn, or similar);
• Experience working with databases (SQL/NoSQL);
• Experience with XGBoost and Deep Learning models
• Experience with deep learning frameworks (TensorFlow, PyTorch, Keras);
• Familiarity with big data tools (e.g., Spark, BigQuery).
• Experience in NLP tasks such as topic modeling
• Understanding of embeddings, vector databases, and language models

• English — Upper-Intermediate or higher.

   

Nice to have:

• Experience with Git;
• Basic understanding of MLOps is a plus;
• Experience with cloud platforms (AWS, GCP, Azure);
• Experience deploying ML models;

We offer:

• Remote and flexible work;
• An international team (Ukraine + Colombia);
• Part-time opportunity;
• Professional growth;
• A supportive and collaborative environment.

Role overview

Partner with sales and delivery to win new data engagements. You'll translate vague client problems into credible, costed solution architectures, lead technical discovery, and present to stakeholders ranging from CTOs to procurement.

Responsibilities

• Lead technical discovery calls; turn business needs into reference architectures and high-level designs
• Build proposals, SoWs, and effort estimates jointly with delivery leads
• Run solution demos, POCs, and architecture walkthroughs for prospects
• Respond to RFPs/RFIs with clear technical narratives
• Stay current on the modern data stack and competitor offerings; advise sales on positioning and trade-offs

Required experience

• 5+ years in data engineering / data architecture, with at least 2 years in a client-facing or presale capacity
• Strong command of cloud data platforms across AWS, Azure, and GCP (at least two hands-on)
• Working knowledge of the major data warehouses and lakehouses: Snowflake, Databricks, BigQuery, Redshift
• Solid grasp of streaming (Kafka, Kinesis), orchestration (Airflow, dbt, Dagster, Prefect), and table formats (Delta, Iceberg)
• Comfortable estimating cost, effort, and risk across architectures you haven't personally built
• Excellent written and spoken English; able to lead a room of senior stakeholders

Nice to have

• Background in BI tooling (Power BI, Tableau, Superset)
• Experience with regulated industries (banking, insurance, healthcare)
• Certifications across two or more cloud/data vendors

We are looking for a Computer Vision Engineer with solid ML/DL experience to join our team on challenging projects.
We consider engineers at Middle and Senior levels - tasks and responsibilities will be adjusted accordingly. 

Required Qualifications:

• 3+ years of experience in computer vision
• High proficiency in Python
• Strong experience with deep learning and the PyTorch framework for computer vision tasks
• Research experience in computer vision with a focus on delivering results
• Ability to work independently or within a small team, with a strong sense of ownership over results

Nice to Have:

• Experience with deep learning solutions for detection, tracking, image retrieval, and segmentation tasks
• Understanding of geometric computer vision principles
• Model optimization: quantization, pruning, neural network compilers
• Hands-on experience implementing low-level CV algorithms
• Experience with sensor fusion (IMU, magnetometer, GNSS, camera)
• Knowledge of C++

We are seeking an experienced Mid/Mid+ Data Scientist with expertise in Large Language Models (LLMs) such as GPT, Claude, and related technologies. The ideal candidate will have a strong background in natural language processing (NLP), machine learning, and deep learning models. They will play a critical role in developing and deploying cutting-edge LLM applications to drive innovation across our product lines.
 

Responsibilities:

• 5+ years of commercial experience as a Data Science / AI Engineer
• Strong Python skills and solid software engineering fundamentals
• Proven experience building high-load, production-grade systems
• 2+ years of experience working with LLM and NLP-related tasks
• Hands-on experience with RAG pipelines and vector databases
• Strong understanding of modern deep learning architectures
• Experience with at least one deep learning framework (TensorFlow or PyTorch)
• Experience with SQL and NoSQL databases
• Good knowledge of Kubernetes
• Experience working with modern AI development tools (e.g., Claude Code, Cursor)
• Familiarity with Model Context Protocol (MCP)
• Experience with production LLM frameworks (e.g., vLLM)
• Experience training or fine-tuning LLMs
• Experience with cloud platforms (AWS, Google Cloud, Azure)
• Participation in Kaggle or similar competitions
• Ukrainian Native, English B2

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.

Join PwC's Data & AI team and help design and deliver the AI and machine learning solutions that drive real business impact. We're growing quickly due to a strong pipeline of client work, and we're hiring across multiple seniority levels — from junior to senior Data Scientists.

Python is the core skill we expect. Depending on your strengths, you may focus on machine learning, statistical modelling, NLP, computer vision, or GenAI. Many roles also include "full-solver" flexibility — contributing where needed, including experimentation, prototyping, deploying models, or working end-to-end on AI use cases using modern platforms (including Microsoft technologies where relevant).

What You'll Do:

• Build AI That Solves Real Problems: Design, develop, train, and evaluate machine learning and statistical models across a wide range of business challenges.
• Turn Messy Data Into Insights: Explore, analyse, and visualize complex datasets to uncover patterns that matter. Perform feature engineering, data preprocessing, and selection to maximize model performance.
• Push the Boundaries With GenAI & NLP: Design and implement solutions leveraging Large Language Models, Retrieval-Augmented Generation (RAG), and NLP techniques.
• Experiment Rigorously, Deploy Confidently: Collaborate with data engineers and platform teams to move models from notebook to production, monitor performance over time, and support continuous retraining and improvement.
• Work Directly With Clients: Collaborate with clients across Western Europe and the USA to understand their business challenges, frame problems as data science opportunities, and communicate findings clearly. 
• Stay Ahead of the Curve: Keep up with the latest in AI/ML research, emerging techniques, and new tools. 

Who We're Looking For:

• Programming Skills (Key Requirement): Strong programming skills in Python (e.g. scikit-learn, TensorFlow, PyTorch, pandas, NumPy, Hugging Face, LangChain). The ability to write clean, maintainable, and reproducible code is essential.
• Machine Learning: Demonstrated hands-on experience building, training, and evaluating ML models. Strong understanding of supervised and unsupervised learning techniques, model selection, hyperparameter tuning, and cross-validation.
• Statistics & Mathematics: Understanding of core statistical concepts, probability, and linear algebra.
• NLP & GenAI (Highly Valued): Experience with natural language processing, text analytics, large language models, prompt engineering, RAG architectures, or other GenAI techniques.
• Computer Vision (Nice to Have): Experience with image processing, object detection, visual reasoning, or satellite imagery analysis is an advantage.
• Data Handling: Proficiency in SQL and experience with data wrangling, cleaning, and transformation.
• Cloud & MLOps (Nice to Have): Experience with cloud platforms (preferably Azure: Databricks, Azure ML, Synapse) or similar services on AWS/GCP is an advantage.
• Professional Background: At least 2–3 years of professional experience in data science, machine learning, applied research, or similar analytical roles.
• Language Skills: English at B2 level or higher.

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

About the role

We are looking for a Senior Data Scientist to lead the evolution of machine learning systems within a high-scale AdTech ecosystem.

This is not a “campaign optimization” role. You will work on the core decision-making systems (DSP level) — where pricing, bidding, pacing, and experimentation interact in real time across billions of events per day.

You will be shaping the “brain” of the platform: a set of interconnected systems where small improvements can have a large business impact.

What you’ll work on

• Pricing & Budget Scalability
  Scale budgets while maintaining performance and controlling overspend
• User Selection Optimization
  Improve CVR through smarter targeting and traffic selection
• Exploration Efficiency
  Reduce wasted spend while preserving learning
• Incrementality Measurement
  Measure true lift vs attributed performance
• Fraud Detection & Filtering
  Improve traffic quality and filtering strategies

What we expect from you

System-level thinking

• Ability to reason about interacting systems, not isolated models
• Understanding of:
  • auction dynamics
  • bidding vs pacing trade-offs
  • feedback loops between models
• Seeing problems beyond segmentation or heuristics

Strong experimentation mindset

• Designing experiments, not just running A/B tests
• Experience with:
  • metric design (proxy vs north star)
  • online vs offline evaluation gaps
  • interference and auction effects
• Ability to translate system changes into measurable impact

Ownership & impact

• Proven track record of driving business impact, not only building models
• Ability to explain:
  • expected vs actual impact
  • why results differ
• Performance accountability mindset

AdTech domain understanding

• Solid understanding of:
  • targeting vs bidding vs supply dynamics
• Experience working close to DSP / auctions/pricing systems

Collaboration maturity

• Ability to work across DS, MLE, and Product
• Understanding trade-offs and constraints
• Experience making decisions in ambiguous environments

Core responsibilities

• Turn ambiguous problems into testable hypotheses
• Design and run offline analysis + online experiments
• Use intermediate metrics to understand system behavior
• Build prototypes and iterate quickly
• Identify where system-level improvements are required
• Collaborate across teams to drive end-to-end impact

Requirements

• 5+ years in Data Science / Machine Learning
• Strong experience in high-frequency systems (AdTech / FinTech / similar)
• Python & SQL proficiency
• Experience with big data tools (Spark, Snowflake, etc.)
• Strong ML background (TensorFlow, PyTorch, or similar)
• Solid foundation in:
  • probability
  • statistics (frequentist / Bayesian)
  • causal inference
• Master’s or PhD in a quantitative field

Nice to have

• Experience with DSP / auctions / pricing systems
• Experience with large-scale experimentation