Diageo - Specialist - Data Science (3-7 yrs)

Job Description :

We are seeking a dynamic Specialist Data Science with 3 to 7 years of total experience to join our enterprise analytics team.

This role is designed for a data scientist who bridges traditional advanced analyticssuch as time-series forecastingwith cutting-edge capabilities in Generative AI and Natural Language Processing (NLP).

In this position, you will work closely with enterprise leadership to design and deploy AI solutions across key corporate functions (Finance, HR, Legal, IT, or Governance).

You will be responsible for translating complex corporate business contexts into robust, scalable, and automated analytical solutions.

Key Responsibilities :

- Design, develop, and implement Generative AI (LLMs, RAG frameworks), NLP, and applied AI solutions to automate and intelligent-ize workflows within corporate functions (e.g., legal document parsing, HR sentiment analysis, IT ticketing automation).

- Build, validate, and maintain high-accuracy Time-Series Forecasting models to support corporate planning, financial budgeting, resource utilization, or risk governance.

- Write clean, production-grade code in Python and PySpark to process large-scale datasets, executing complex data transformations using SQL within Databricks.

- Architect and deploy end-to-end data science pipelines natively within Azure (or equivalent cloud platforms like AWS/GCP), ensuring security, data governance, and scalability.

- Act as a strategic partner to corporate business units.

- Deeply understand the nuances of functions like Finance, HR, Legal, or IT, and translate their operational challenges into technical data science roadmaps.

- Monitor the performance of deployed predictive and generative models, ensuring data drift management, ethical AI compliance, and continuous model retraining.

Required Skills & Qualifications:

- GenAI & NLP (Mandatory): 1 to 2 years of hands-on experience building solutions using Large Language Models (LLMs), prompt engineering, fine-tuning, embeddings, text extraction, or semantic search.

- Strong foundational knowledge and hands-on experience with Time-Series Forecasting techniques (e.g., ARIMA, Prophet, Deep Learning for time-series, or tree-based ensembles applied to temporal data).

- Advanced proficiency in Python, robust experience with PySpark for distributed computing, and expert-level SQL skills for data extraction and manipulation.

- Strong hands-on experience developing within Databricks environments (Notebooks, Delta Lakes, MLflow).

- Proven experience leveraging Azure cloud services (e.g., Azure Data Factory, Azure ML, Azure OpenAI Service) or equivalent cloud providers (AWS/GCP) for machine learning workflows.

- Solid domain awareness in at least one enterprise pillar: Finance (e.g., spend analysis, variance forecasting), HR/People Analytics (e.g., attrition modeling), Legal/IT, or Governance Analytics.

- Proven ability to listen to a business problem, understand the context, map the available data, and build a tailored AI solution without needing highly rigid technical specifications.

- 3 7 years of professional experience in data-driven environments.

- Minimum of 1 2 years of dedicated, hands-on experience specifically in GenAI, NLP, or applied AI frameworks.

- Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, Management Information Systems (MIS), or a highly quantitative field