Data Scientist (AI&Data)

At the AI&Data, we work locally and globally with over 250 Poland-based specialists. Our expertise spans data architecture and sectoral specialization. We collaborate with tech partners like Microsoft, AWS, Google, Oracle, and Snowflake to implement cutting-edge solutions. We provide comprehensive support from strategy definition to solution implementation and development, covering all aspects of Data & Analytics.

THE WORK

As a Data Scientist, you will design and deliver data-driven solutions that turn complex enterprise data into actionable insights and intelligent products for leading global companies. We’re looking for people who combine strong analytical and statistical foundations with practical engineering skills – and who are eager to leverage GenAI as a force multiplier in their data science workflow.

You will:

• Build and deploy machine learning models and analytical solutions that solve real business problems at scale for enterprise clients
• Design and implement advanced analytics pipelines – from data exploration and feature engineering through model training, evaluation, and production deployment
• Leverage GenAI and LLMs to augment data science workflows: conversational analytics, Text-to-SQL, automated insight generation, and intelligent data exploration over enterprise datasets
• Translate business requirements into data science approaches – selecting the right methods, validating assumptions, and communicating results to both technical and non-technical stakeholders
• Collaborate with engineers, architects, and consultants on cross-functional project teams, contributing to solution design and technical direction

Flexible: The work location for this role may include a mix of working remotely (most of the time), onsite at a client or in an Accenture office – depending on specific project circumstances. With all our roles, there is some in-person time for collaboration, learning and building relationships with clients, peers, leaders, and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.

• A permanent employment contract
• Individual support of a People Lead and a clearly defined path of professional development, including the possibility of a session with a Coach
• A comprehensive training package, including: soft skills, technical and language training, access to e-learning platforms, Gallup test, GenAI training, possibility of co-financing courses and certifications
• Employee Assistance Program offering legal, financial and psychological consultations
• Employee Share Purchase Plan – employees who own company shares are automatically eligible for quarterly dividends
• Paid employee referral program
• Private medical care and life insurance
• Access to the Worksmile benefits platform (including the Multisport card)

Interview Note: We value practical skills. During the technical interview, we’ll give you a real problem to solve and debug together – using your preferred development setup, including any AI-assisted tools you work with day to day.

• Min. 3 years of commercial experience in Data Science, Machine Learning, or a related analytical role
• Strong Python skills and advanced SQL knowledge
• Solid foundation in statistics, machine learning, and predictive modeling – able to select the right approach and validate results rigorously
• Experience with ML frameworks and libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow)
• Practical experience with data wrangling, feature engineering, and working with large-scale datasets
• Familiarity with LLMs and Generative AI – understanding how to leverage foundation models for analytical tasks (e.g., Text-to-SQL, data summarization, conversational analytics)
• Proficiency with AI-assisted development tools (e.g., Cursor, Copilot, or similar) – we expect these to be a core part of your daily workflow, not an occasional add-on
• Experience with cloud platforms (AWS, Azure, or GCP) for model deployment and data processing
• Good command of English (min. B2+)

BONUS POINTS IF YOU HAVE

• Experience building NLP solutions or working with text data at scale
• Hands-on experience with RAG pipelines, embeddings, or vector databases in analytical contexts
• Familiarity with MLOps practices, experiment tracking (e.g., MLflow, Weights & Biases), and CI/CD for ML models
• Experience with data visualization tools and building analytical dashboards (e.g., Power BI, Tableau, Streamlit)
• Knowledge of containerization and API tooling (Docker, FastAPI, Flask)
• Understanding of Responsible AI principles and model fairness, explainability, and bias mitigation
• Contributions to open-source projects, published research, or Kaggle competition experience