Experience:

• 5–8 years of progressive experience in data science, machine learning engineering, AI development, or applied research roles
• 3+ years of experience building and deploying ML models in production environments
• 3+ years of experience with cloud data platforms such as Databricks, Azure ML, AWS SageMaker or equivalent

Qualification:

• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering (BE/BTech), or related quantitative field
• Master's degree (MS/MTech) in Machine Learning, AI, Data Science, or related discipline preferred

Role Focus:

• Design, develop, and deploy machine learning and statistical models for business use cases including forecasting, customer segmentation, pricing optimization, automation, cross-sell, and churn prediction
• Perform exploratory data analysis, feature engineering, and data preparation using diverse enterprise data sources
• Build and maintain scalable ML pipelines using Databricks, MLflow, and cloud technologies
• Develop NLP solutions such as text classification, entity extraction, sentiment analysis, and summarization
• Implement model governance practices including versioning, A/B testing, drift monitoring, retraining, and documentation
• Design and develop agentic AI solutions, conversational AI experiences, and intelligent automation workflows
• Evaluate and apply emerging AI technologies including LLMs, RAG, prompt engineering, and cognitive automation
• Build and scale AI proof-of-concepts from ideation through production deployment
• Develop SQL and Python-based ETL/ELT processes supporting analytics and AI/ML development on Databricks
• Build and maintain curated datasets, feature stores, and data assets
• Collaborate with data engineering and governance teams to ensure data quality, lineage, security, and compliance
• Support migration and modernization of analytics and data science solutions onto Databricks
• Work closely with stakeholders across Sales, Marketing, Customer Care, Pricing, and Strategy to identify opportunities and deliver data science solutions
• Translate analytical results into actionable insights through data storytelling, visualizations, and executive-ready presentations
• Present recommendations to technical and non-technical audiences and support adoption of AI-driven solutions
• Contribute to business case development, feasibility assessments, and value estimation for new AI initiatives
• Ensure AI/ML solutions comply with enterprise standards for responsible AI, privacy, governance, bias mitigation, and regulatory requirements
• Develop KPIs and monitoring frameworks to track model performance, adoption, and business value
• Stay current on AI/ML advancements and share knowledge through mentoring, documentation, reviews, and community engagement
• Contribute reusable best practices, frameworks, and lessons learned to strengthen team capabilities

Additional responsibilities:

• Partner with AI leadership to assess technologies and recommend solutions aligned with business priorities

Nice to have:

• Master's degree in related discipline
• Experience with agentic AI frameworks, LLM application development, and conversational AI

More skills:

SQL, Databricks, Azure ML, AWS SageMaker, MLflow, NLP techniques, text classification, named entity recognition, sentiment analysis, LLM fine-tuning, time-series forecasting, MLOps, CI/CD for ML, experiment tracking, automated retraining, data warehousing, ETL/ELT, incremental loading, data governance, Power BI, Tableau, agentic AI frameworks, LLM application development

Other:

• Role reports to India-based Data Analytics & Data Science Delivery Manager
• Collaborates with NA-based Data & Analytics product owner, Channel AI Principal, Channel BU leadership, global DIA teams, and cross-functional stakeholders across AMER, EMEA, and APAC
• Workplace type: Onsite
• Travel required: None
• Values: Integrity, Accountability, Inclusion, Innovation, Teamwork