Data Scientist

About the role

We are looking for a Data Scientist to lead data readiness, preparation, and AI/ML data quality initiatives for enterprise clients. You will act as the critical conduit between client business needs, our agentic AI platform, and the practical requirements for data discovery, hygiene, labeling, and model‑readiness.

Key responsibilities

• Assess enterprise client data landscapes, identify quality issues, and define preparation work needed for AI value creation.
• Design and lead data readiness workstreams covering discovery, profiling, cleansing, normalization, deduplication, enrichment, annotation, labeling, transformation, and structuring.
• Translate client use cases into clear data requirements for AI models, dashboards, and Intelligent Command Centre solutions.
• Collaborate with AI Infrastructure, Product, and UX teams to ensure data pipelines, schemas, embeddings, and evaluation datasets are fit for purpose.
• Define data quality frameworks, acceptance criteria, validation checks, and readiness scorecards.
• Support creation of high‑quality training, evaluation, and fine‑tuning datasets for open‑source and LLM‑agnostic models.
• Act as the technical bridge between clients, internal teams, and third‑party data partners, overseeing quality and timelines.
• Build reusable playbooks, templates, checklists, data dictionaries, and readiness methodologies.
• Participate in client discovery workshops, pilot planning, and delivery reviews.
• Ensure sensitive client data is handled with appropriate governance, privacy, security, and compliance.

Required profile

• 3–5 years of experience in data science, applied machine learning, data engineering, analytics engineering, or AI/ML delivery.
• Experience in enterprise or consulting environments is preferred.
• Strong hands‑on experience preparing real‑world data for machine learning models.

Required skills

• Data engineering
• Machine learning
• Analytics engineering
• Data preparation
• Data quality assessment