Lead - Data Sciences & Analytics

• Associate Manager - Data Science & Analytics (O5)
• Business: Adani Group
• Department: Digital Transformation / Data Science & Analytics
• Location: Ahmedabad / Mumbai / Project Locations
• Key Responsibilities Data Analytics & Business Intelligence
• Analyze large and complex datasets from multiple sources to generate actionable business insights.
• Design and develop dashboards, KPIs, scorecards, and reporting frameworks for leadership review.
• Establish data governance standards, data quality controls, and reporting accuracy mechanisms.
• Conduct trend analysis, forecasting, and root-cause analysis to support key business decisions.

Data Science & Machine Learning

• Develop predictive and prescriptive analytics models to improve business outcomes.
• Build and deploy Machine Learning (ML) and Artificial Intelligence (AI) solutions for various business functions.
• Work on demand forecasting, risk analytics, productivity optimization, cost reduction, and resource utilization models.
• Evaluate emerging AI technologies and recommend innovative use cases across the organization.

Data Engineering & Automation

• Collaborate with technology teams to build scalable data pipelines and analytics platforms.
• Automate recurring reports and analytical processes using advanced data tools.
• Ensure seamless integration of data across ERP, CRM, HRMS, Project Management, and operational systems.

Stakeholder Management

• Partner with Business Heads, Functional Leaders, and Project Teams to understand analytical requirements.
• Translate business challenges into data science use cases and measurable outcomes.
• Present analytical findings and recommendations to senior leadership in a clear and impactful manner.

Innovation & Digital Transformation

• Drive AI-led digital transformation initiatives across business units.
• Identify opportunities for process optimization through advanced analytics.
• Benchmark industry best practices and implement innovative analytical frameworks.

Required Qualifications

B.E./B.Tech / MCA / M.Tech in Computer Science, Information Technology, Data Science, Statistics, Mathematics, Analytics, or related discipline.

Master's degree in Data Science, Business Analytics, AI/ML, or equivalent preferred.

Experience

• 8-12 years of experience in Data Analytics, Data Science, Business Intelligence, or AI/ML domains.
• Experience working on enterprise-scale analytics projects.
• Exposure to infrastructure, manufacturing, construction, energy, logistics, or EPC sectors will be preferred.

Technical Skills

• Strong proficiency in Python, R, SQL, and data analytics tools.
• Experience with Machine Learning, Deep Learning, NLP, and Generative AI applications.
• Hands-on experience with Power BI, Tableau, QlikView, or similar BI platforms.
• Knowledge of cloud platforms such as Azure, AWS, or GCP.
• Experience with big data technologies including Spark, Hadoop, Databricks, or similar ecosystems.
• Understanding of data warehousing, ETL, and data governance frameworks.

Behavioral Competencies

Strategic Thinking

Business Acumen

Analytical & Problem-Solving Skills

Stakeholder Management

Innovation & Continuous Improvement

Leadership & Team Collaboration

Result Orientation

Communication & Presentation Skills

Key Deliverables

Enterprise Analytics Strategy Execution

AI & Machine Learning Solution Deployment

Automated Reporting & Dashboarding

Predictive Analytics Models

Data Governance Compliance

Business Insight Generation

Operational Efficiency Improvements

Digital Transformation Enablement

Grade: O5 - Associate Manager

Required Qualifications

B.E./B.Tech / MCA / M.Tech in Computer Science, Information Technology, Data Science, Statistics, Mathematics, Analytics, or related discipline.

Master's degree in Data Science, Business Analytics, AI/ML, or equivalent preferred.

Experience

• 8-12 years of experience in Data Analytics, Data Science, Business Intelligence, or AI/ML domains.
• Experience working on enterprise-scale analytics projects.
• Exposure to infrastructure, manufacturing, construction, energy, logistics, or EPC sectors will be preferred.