Senior Data Scientist
Infosys
- Programming: python (pandas, numpy), Spark, Git
- Modeling: supervised & unsupervised learning
- Infrastructure : Cloud (Azure is a plus)
- Data Science tools/modules: Databricks / MLFlow/ Mosaic. Microsoft / Foundry
- Solid understanding of statistics, causal inference, and optimization.
- Collaborate with business leaders to understand business needs and translate them into actionable AI products.
- Apply state-of-the-art algorithms and predictive models (Machine Learning/Deep Learning) to answer business problems.
- Model Development: Build, validate, and deploy advanced machine learning models (e.g., CatBoost, XGBoost, deep learning) for forecasting, optimization, and recommendation systems.
- Causal Inference & Experimentation: Apply causal inference techniques and design experiments to measure the impact of interventions.
- Data Strategy: Partner with data engineers to ensure robust data pipelines and scalable architectures.
- Business Impact: Translate complex analytics into actionable insights for stakeholders in business like QFS, R&I, Ops, Sales, Marketing.
- Innovation: Explore and implement state-of-the-art AI techniques (e.g., generative AI, reinforcement learning) to solve business challenges.
- Mentorship: Guide junior data scientists and foster best practices in coding, model governance, and documentation.
- Design GenAI Evaluation Frameworks GenAI, Agentic and classic ML.
- Implement robust evaluation frameworks within key AI providers, including offline metrics, error analysis, and bias detection.
- More than. 7 years of experience in Data Science within a fast-paced and complex business setting, preferably working as a Data Scientist.
- A MSc, PhD or other Advanced Degree in a field linked to computer science, applied mathematics, statistics, machine learning, or closely related fields
- Experience in Fast-Moving Consumer Goods (FMCG) industry is a plus.