Advisory Consultant (I9)
Role details
Job location
Tech stack
Job description
We are seeking a senior Data Scientist to lead the design and implementation of advanced analytical solutions that drive strategic business value for our clients. In this role, you will transition beyond building isolated models to architecting "Compound AI Systems." You will be responsible for turning ambiguous business challenges into scalable, production-ready machine learning (ML) and Large Language Model (LLM) applications. As a senior member of the team, you will act as a bridge between technical execution and business strategy, mentoring junior talent while ensuring our AI projects & initiatives are ethical, robust, and impactful.
Responsibilities
You will:
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Problem Framing: Translate complex business needs into end-to-end data products, from discovery and data acquisition to deployment and continuous monitoring. Design and build integrated systems combining predictive models, RAG pipelines, foundation models, and GenAI solutions.
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Scientific Rigor: Lead A/B testing, multivariate experiments, and causal inference to measure product impact; collaborate on reproducible feature pipelines.
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Team Growth: Mentor junior and mid-level data scientists, conduct code reviews, and foster technical excellence. Establish best practices for validation, version control, and documentation, and communicate insights to executives through clear data storytelling.
Requirements
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Programming: Advanced Python (NumPy, Pandas, ML/DL frameworks) and expert SQL
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Generative AI: LLM orchestration (LangChain, LlamaIndex, LangGraph, etc.) and model fine-tuning. Strong grounding in Bayesian methods and uncertainty quantification
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Production: Model deployment with FastAPI/Flask, Docker, and Kubernetes
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Orchestration & MLOps: ML pipelines using Airflow or Kubeflow with monitoring and HITL feedback. Cloud ML platforms (SageMaker, Azure ML, Vertex AI) and vector DBs (Pinecone, Milvus, Weaviate)
Desirable Requirements
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Master's or PhD in a quantitative field (Computer Science, Statistics, Mathematics, Physics, or Economics). Equivalent professional experience will be considered. 12-18 years of experience in a Data Science role, with at least 5 years at a Senior level delivering models to production.
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Proven track record of linking data science outcomes to KPIs such as revenue growth, churn reduction, or operational efficiency.Exceptional problem-solving skills, intellectual honesty, and the ability to work in an agile, fast-paced environment.