Mid Data Scientist (Data&AI)

At the AI&Data, we work locally and globally with over 200 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 specific path of professional development, as well as the possibility of a session with a Coach.
• A wide training package (soft, technical, and language training offer, access to the e-learning platforms, Gallup test, GenAI training, possibility of co-financing courses, and certification).
• Employee Assistance Program - legal, financial, and psychological consultations.
• Accenture employees eligible for the Employee share purchase plan automatically become eligible for quarterly dividends if they own company shares.
• Paid employee referral program.
• Private medical care and life insurance.
• Access to the Worksmile platform (possibility of using a wide range of products and services, including the Multisport card).

• 3+ years of relevant professional experience in Data Science, Machine Learning or Data Engineering, with strong Python skills and practical experience with PySpark and distributed data processing.
• Solid foundation in machine learning, predictive modeling, statistics and probability, including experience with data wrangling and feature engineering, and at least one ML framework such as scikit-learn, XGBoost, PyTorch or TensorFlow.
• Strong understanding of statistics and probability theory
• Hands-on experience with MLOps, including experiment tracking tools such as MLflow or Weights & Biases and CI/CD practices for ML models.
• Strong experience with cloud platforms (AWS, Azure, or GCP) for model deployment and data processing.
• Familiarity with LLMs and Generative AI and their use in analytical scenarios, together with proficiency in AI-assisted development tools such as Cursor, Copilot or similar.
• Bachelor’s degree or higher in Computer Science, Mathematics, Statistics, Data Science or another related technical field,
• Good command of English at B2+ level.

BONUS POINTS IF YOU HAVE:

• Experience with Databricks and/or building NLP solutions and processing text data at scale.
• Hands-on experience with RAG pipelines, embeddings or vector databases, particularly for analytical use cases.
• Experience with data visualization tools such as Power BI, Tableau or Streamlit, containerization/API technologies such as Docker, FastAPI or Flask, Responsible AI practices, or contributions to open-source projects, published research or Kaggle competitions.

Research indicates that some candidates, especially the most diverse ones, may hesitate to apply for positions if they don't meet all requirements. If you believe you possess the necessary skills, even if not meeting every requirement, we wholeheartedly encourage you to submit your application.