{"id":4199480,"url":"https://alion.io/job/mahindra-logistics-lead-analytics-data-science","title":"Lead - Analytics & Data Science","company":{"id":2073017,"name":"Mahindra Logistics","domain":"mahindralogistics.com","url":"https://alion.io/company/mahindralogistics","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Darwinbox","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Function Calling","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Power BI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Superset","optional":false},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-11-12T21:35:00Z","employer_posted_date":null,"last_verified_at":"2026-11-12T21:35:00Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"We are looking for an experienced Data, Business Intelligence (BI) & AI Solutions Lead to drive the development of scalable data solutions, business intelligence platforms, automation initiatives, and AI-powered applications. The ideal candidate will combine strong technical expertise in Python, cloud technologies, data engineering, BI tools, Generative AI, and Agentic AI with proven leadership and stakeholder management skills.\n\nThe role involves translating business requirements into actionable insights and scalable technology solutions while leveraging AI to improve productivity, operational efficiency, and decision-making.\n\nKey Responsibilities:\nBI & Analytics: Design, develop, and maintain interactive dashboards, reports, and KPI frameworks using Power BI, Amazon QuickSight, Apache Superset, or similar BI tools.\nPython Development: Develop robust Python-based solutions for data processing, automation, analytics, AI/ML, and business problem-solving.\nData Engineering: Build and optimize ETL/ELT pipelines, data integrations, APIs, data models, and data quality frameworks.\nCloud Data Solutions: Design and implement cloud-based data solutions using AWS and/or Azure, including storage, compute, data platforms, and workflow orchestration.\nAI & Generative AI: Develop AI-powered applications using LLMs, Retrieval-Augmented Generation (RAG), prompt engineering, and relevant AI frameworks.\nAgentic AI: Design and implement AI agents, multi-agent workflows, tool/function calling, and agent orchestration to automate complex business processes.\nProcess Automation: Identify and implement intelligent automation opportunities to streamline workflows, reduce manual effort, and improve operational efficiency.\nSolution Architecture: Translate business requirements into scalable, secure, maintainable, and cost-effective data and AI solutions.\nAI-Driven Productivity: Identify and implement practical AI use cases to improve reporting, analysis, coding, documentation, and decision-making.\nTechnical Leadership: Lead and mentor technical teams, establish engineering best practices, prioritize initiatives, and ensure timely delivery of high-quality solutions.\nStakeholder Management: Collaborate with business leaders, product teams, and technology stakeholders to understand requirements, define solution roadmaps, and communicate outcomes.\nContinuous Improvement: Evaluate emerging technologies, frameworks, and tools to improve the organization's data, analytics, AI, and automation capabilities.\n\nRequired Skills & Qualifications:\nStrong hands-on experience in Python programming, data processing, and solution development.\nProven expertise in BI and analytics tools such as Power BI, Amazon QuickSight, or Apache Superset.\nStrong understanding of ETL/ELT, data engineering, data modeling, APIs, and data pipeline development.\nExperience with AWS and/or Azure cloud services and cloud-based data platforms.\nPractical experience with Generative AI, LLMs, RAG, and prompt engineering.\nUnderstanding of Agentic AI concepts, AI agents, tool/function calling, and workflow orchestration.\nExperience in process automation and developing scalable business solutions.\nStrong analytical, problem-solving, and solution design skills.\nExcellent communication, stakeholder management, and cross-functional collaboration abilities.\nDemonstrated leadership experience in team management, mentoring, prioritization, and delivery.\n\nPreferred Qualifications:\nExperience deploying and maintaining production-grade AI and data applications.\nKnowledge of data governance, security, performance optimization, and responsible AI practices.\nFamiliarity with machine learning frameworks, vector databases, and AI application development frameworks.\nExperience integrating enterprise systems through APIs and automated workflows.\nAbility to assess business processes and identify high-impact AI and automation opportunities.\nExperience managing multiple projects and delivering measurable business outcomes.\n\nKey Competencies:\nBusiness Intelligence & Data Analytics\nPython & Data Engineering\nCloud Data Architecture\nGenerative AI & Agentic AI\nIntelligent Process Automation\nData & AI Solution Design\nTechnical Team Leadership\nStakeholder & Delivery Management\nAI-Driven Business Transformation\n\nSuccess Metrics:\nDelivery of reliable, scalable, and user-friendly BI dashboards and data solutions.\nImproved data quality, reporting accuracy, and accessibility of business insights.\nReduction in manual effort through automation and AI-powered workflows.\nSuccessful implementation and adoption of AI and Agentic AI applications.\nImproved team productivity, delivery timelines, and stakeholder satisfaction.\nDemonstrable business value through efficiency gains, cost optimization, and better decision-making.\nSkills\nAWS, Amazon QuickSight, Apache Superset, Azure, Power BI, 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