Infosys—Senior Data Scientist

Job description

Description: · 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. Requirements: This role will focus on designing and deploying cutting-edge machine learning and AI solutions to drive business impact across Research & Innovation, Quality & Food Safety, and Sales. You will work on high-impact projects such as predictive modeling, causal inference, optimization, and generative AI applications to unlock insights and accelerate decision-making. Location for this position is Barcelona. Responsibilities: · 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. Skills: We are looking for people having the following technical skills: · 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.