Data and Analytics Lead

Opella; Hyderabad; On-site; INR 400,000 - 700,000; Full time

Job summary

Opella }}in India seeks a Data and Analytics Lead to shape and execute the data, analytics, and AI strategy for AMEA. The role combines hands-on delivery of data science and GenAI with bridging AMEA business, regional Digital Leads, and Opella's global initiatives.

You will represent AMEA in cross-regional conversations, manage diverse stakeholders, and drive end-to-end AMEA initiatives, enabling regional leadership to focus on strategy and scale.

Qualifications

• Hands-on data science and AI delivery experience.
• Experience across multiple regions or matrixed roles is a plus.
• FMCG, Pharma, or Healthcare exposure not required.

Responsibilities

• Act as AMEA point of contact for data, data science, and AI matters.
• Coordinate regional Digital Leads and align priorities with regional roadmap.
• Manage multiple stakeholder conversations across countries and functions.
• Identify reusable or adaptable global initiatives for AMEA.
• Design, build, and deploy data science and GenAI solutions from prototype to production.
• Provide regular updates on regional initiatives, blockers, and wins.

Skills

Python

SQL

ML/GenAI

LLMs

Data Science

Forecasting

Tools

Snowflake

Databricks

Airflow

DBT

Azure OpenAI

Anthropic Claude

LangGraph

Semantic Kernel

MCP

Job description

We are seeking a highly experienced and strategic leader to fill the role of Data and Analytics Lead. This role is pivotal in shaping and executing our data, analytics, and AI strategy for AMEA region. The hired individual will be the operational backbone of our Data, AI & Innovation charter across AMEA. This role sits close to the ground — building and shipping data science, AI, and GenAI solutions — while also acting as the bridge between the AMEA business, regional Digital Leads, and Opella's global Data & AI initiatives. You'll represent the AMEA point of view in cross-regional conversations, keep multiple stakeholder relationships warm and moving in parallel, and continuously scan global projects for what can be adapted or reused locally instead of rebuilt from scratch. Over time, this person should be capable of independently owning AMEA-specific initiatives end-to-end, freeing up regional leadership to focus on strategy and scale.

Key Responsibilities

• AMEA Point of Contact: Act as the day-to-day representative for AMEA on data, data science, and AI matters — surfacing regional needs, constraints, and priorities into broader Opella conversations.
• Regional Digital Lead Coordination: Build and sustain working relationships with Digital Leads across AMEA countries, translating local business problems into shared data/AI priorities and keeping them aligned with the regional roadmap.
• Continuous Stakeholder Management: Comfortably manage several concurrent, ongoing stakeholder conversations across countries and functions — following up, unblocking, and keeping many parallel threads moving without anything falling through the cracks.
• Global-to-Regional Synergy Scouting: Track global Data, AI, and GenAI initiatives, and proactively identify which are relevant, reusable, or adaptable for AMEA — avoiding duplicate builds and accelerating regional delivery by leveraging global investment.
• Hands-On Delivery: Design, build, and deploy data science and GenAI solutions (from prototype to production) — this is a builder role, not purely an oversight one.
• Reporting & Visibility: Provide clear, regular updates on regional initiatives, blockers, and wins to regional and global stakeholders.

Qualifications -

Experience

• 12-15 years total experience in Data Science, AI/ML, or Analytics, with demonstrable hands-on delivery (not purely strategy/oversight).
• Experience working across multiple countries/cultures or in a regional/matrixed role is a strong plus.
• FMCG, Pharma, or Healthcare industry exposure is a plus, not mandatory.

Skills

• Strong hands-on technical skills: Python, SQL, and modern ML/GenAI frameworks.
• Working knowledge of cloud and data platforms — Snowflake, Databricks, Airflow, DBT, or equivalent; AWS/Azure familiarity a plus.
• Strong foundation in data science and machine learning (Python, SQL, statistical modeling, forecasting); hands-on experience with Generative AI and LLMs (prompt engineering, RAG, fine-tuning) using platforms like Azure OpenAI or Anthropic Claude; working knowledge of MCP (Model Context Protocol) and agentic AI frameworks (LangGraph, Semantic Kernel, or similar) to connect AI assistants to enterprise systems; familiarity with cloud data platforms (Snowflake, Databricks, Azure/AWS).
• Applied / Business Skills
• Translating ambiguous regional business problems into scoped data/AI solutions
• Cross-cultural stakeholder communication and the ability to manage several parallel conversations
• Pragmatic build-vs-reuse judgment — spotting when a global asset can be adapted rather than rebuilt
• Excellent stakeholder communication — able to manage multiple relationships simultaneously across geographies and translate technical work into business language.
• Self-directed and comfortable with ambiguity — able to take a loosely scoped regional problem and drive it to a solution independently.
• Collaborative mindset — genuinely curious about global initiatives and motivated to adapt rather than reinvent.