Data Analyst, Predictive Analytics, India- X Delivery

BCG BCG · Consulting · Bengaluru, Karnataka, India +1 · Technology and Engineering

This role involves working with consulting teams on advanced analytics and AI topics, leveraging analytical methodologies to deliver value. The Data Analyst will gather requirements, design, develop, and support analytic solutions, with a focus on predictive modeling, cloud platforms, and familiarity with LLMs, GenAI, agentic AI frameworks, and evaluation metrics. The role requires strong programming skills in Python and SQL, experience with data visualization, ML deployment tools, and big data technologies.

What you'd actually do

  1. Collaborate with case teams to gather requirements, specify, design, develop, deliver and support analytic solutions serving client needs.
  2. Provide technical support through deeper understanding of relevant data analytics solutions and processes to build high quality and efficient analytic solutions.
  3. Communicating analytical insights through sophisticated synthesis and packaging of results (including PowerPoint presentation, Documents, dashboard and charts) with consultants, collects, synthesizes, analyses case team learning & inputs into new best practices and methodologies
  4. Build collateral of documents for enhancing core capabilities and supporting reference for internal documents; sanitizing confidential documents and maintaining a repository
  5. Imparts technical trainings to team members and consulting cohort

Skills

Required

  • Statistics (concepts & methodologies like hypothesis testing, sampling, etc.)
  • Data mining and predictive modeling (Linear Regression/Bayesian, Classification (Logistic regression, Decision trees/Random Forest/Boosted Trees, etc.), Clustering (K-means, DBSCAN, etc.), Timeseries (SARIMAX/Prophet), etc.)
  • Cloud providers (Azure, AWS, GCP)
  • Auto ML solutions (Sage Maker, Azure ML etc.)
  • LLMs, NLP, and GenAI concepts
  • RAG pipelines (chunking, embedding, semantic search, and retrieval strategies)
  • Agentic AI frameworks (LangChain/LangGraph, AutoGen)
  • Tool-calling, multi-agent orchestration, task decomposition, memory/context management, and human-in-the-loop design
  • AI model evaluation frameworks (Phoenix Evals, RAGAS)
  • Experimentation metrics for LLM/RAG systems
  • Python
  • SQL
  • Data Visualization (Tableau, QlikView, Power BI, Streamlit)
  • ML Deployment tools (Airflow, MLflow Luigi, Docker etc.)
  • Big data technologies (Hadoop ecosystem, Spark)
  • Data warehouse solutions (Teradata, Azure SQL DW/Synapse, Redshift, BigQuery, Snowflake/Snowpark, etc,)
  • Version Control (Git/Github/Git Lab)
  • MS Office (Excel, PowerPoint, Word)
  • Coding IDE (VS Code/PyCharm)
  • AI Coding Assistants (Cursor, Claude Code, GitHub Copilot)
  • GenAI tools (OpenAI, Anthropic, Google PaLM/BERT, Hugging Face, etc.)
  • Communicates analytical insights clearly and confidently to both technical and non-technical stakeholders
  • Building analytical solutions and delivering tangible business value for clients

Nice to have

  • PySpark
  • R
  • SAS

What the JD emphasized

  • Strong hands-on data mining and predictive modeling experience
  • Strong experience in at least one of the prominent cloud providers (Azure, AWS, GCP) and working knowledge of auto ML solutions (Sage Maker, Azure ML etc.)
  • Familiarity with LLMs, NLP, and GenAI concepts (OpenAI, Anthropic, Hugging Face) including RAG pipelines — chunking, embedding, semantic search, and retrieval strategies
  • Familiarity with agentic AI frameworks (LangChain/LangGraph, AutoGen) including tool-calling, multi-agent orchestration, task decomposition, memory/context management, and human-in-the-loop design
  • Familiarity with AI model evaluation frameworks (Phoenix Evals, RAGAS) and experimentation metrics for LLM/RAG systems
  • Python, SQL (Must haves)

Other signals

  • familiarity with LLMs, NLP, and GenAI concepts
  • familiarity with agentic AI frameworks
  • familiarity with AI model evaluation frameworks