Data Scientist

Virtusa is seeking a highly experienced Data Scientist (T2) to join their AI Center of Excellence in Poland. The role involves designing, developing, and deploying sophisticated machine learning and generative AI solutions using the full Google Cloud (GCP) ecosystem.

• 8–10 years of experience as a Data Scientist or ML Engineer with production-grade AI solutions.
• Mastery of Python and its scientific ecosystem (NumPy, Pandas, Scikit-learn, SciPy, Matplotlib).
• Expert-level SQL skills with experience querying petabyte-scale data in Google BigQuery.
• Deep hands-on experience with Vertex AI (AutoML, Pipelines, Model Registry, Training) and Google Cloud Storage.
• Practical experience building applications with LangChain or LlamaIndex.
• Proven expertise in RAG architectures, including vector embeddings and similarity search logic.
• Advanced prompt engineering skills for optimizing LLM outputs.
• Comprehensive understanding of supervised, unsupervised, and reinforcement learning algorithms and their statistical foundations.
• Strong knowledge of Neural Networks and experience with TensorFlow or PyTorch.
• Experience with MLflow or Kubeflow for experiment tracking and model deployment.
• Familiarity with Docker and Kubernetes for containerized ML workloads.
• Basic understanding of RESTful APIs and microservices.
• Proficiency in Git, unit testing for ML code, and reproducible research practices.
• Master’s or PhD in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field.
• Exceptional analytical thinking and ability to explain complex statistical results to non-technical stakeholders.
• English language proficiency at C1 level.

• Lead the design and implementation of complex ML algorithms (classification, regression, clustering) and Deep Learning models to solve high-impact business problems.
• Architect and deploy Generative AI solutions, including RAG (Retrieval-Augmented Generation) pipelines.
• Design advanced prompt engineering strategies and work with LLM APIs (Vertex AI, OpenAI) to build intelligent agents.
• Utilize Vertex AI for the full model lifecycle—from experimentation in notebooks to training, tuning, and deployment.
• Leverage BigQuery for large-scale data analysis and Cloud Storage for unstructured data management.
• Collaborate with Data Engineers to build scalable ETL/ELT pipelines.
• Perform advanced feature engineering and data preparation on massive, complex datasets.
• Oversee the transition of models from research to production.
• Ensure model stability through monitoring, drift detection, and automated retraining loops.
• Act as a technical consultant to Architects and Product Owners.
• Mentor junior data scientists and engineers, ensuring adherence to best practices in experimental design and code quality.