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Full-Stack Data Scientist / Ml Engineer
Full-Stack Data Scientist / Ml EngineerITJobCafe, Inc. • Hyderabad, Republic Of India, IN
Full-Stack Data Scientist / Ml Engineer

Full-Stack Data Scientist / Ml Engineer

ITJobCafe, Inc. • Hyderabad, Republic Of India, IN
7 days ago
Job description

A fast-growing consumer products company in Los Angeles, CA is seeking a Full-Stack Data Scientist / ML Engineer to own internal data infrastructure, AI automation, knowledge systems, and workflow optimization. This role will continue and expand the work of our current AI / data lead and will have direct impact across operations, sales, customer support, and product development.

This is a high-visibility, high-autonomy position reporting directly to the CEO.

What You’ll Do

AI & Automation (Primary Focus)

  • Build and maintain internal AI agents that support quoting, product lookup, workflow automation, and exception handling.
  • Develop NLP systems to automatically parse customer inquiries , classify account types, and identify action routing.
  • Maintain and grow an internal LLM-powered knowledge base that captures business rules, supplier constraints, SKU attributes, and operational exceptions.

Data Engineering & ETL Pipelines

  • Design and own production-grade ETL pipelines across CRM, accounting, supplier data, SKU catalogs, and operational datasets.
  • Build reliable data models that unify siloed systems, enabling high-quality analytics and automation.
  • Implement automated data-cleaning processes that support daily operations and decision-making.
  • Internal Tools & Script Development

  • Develop Python tools and micro-automations for pricing logic, invoice workflows, sample handling, customer communication, and data synchronization.
  • Create internal dashboards, utilities, and command-line workflows that support sales, operations, and leadership.
  • Serve as the primary builder of internal automation infrastructure.
  • Operations & Process Analytics

  • Analyze operational bottlenecks and performance trends across production timelines, shipping, and customer response cycles.
  • Provide insights that directly improve efficiency, speed, and customer experience.
  • Cross-Functional Collaboration

  • Work closely with leadership and operations teams to identify automation opportunities.
  • Translate evolving, fast-paced business rules into robust data logic and system behavior.
  • Document internal processes and maintain reliable technical infrastructure.
  • What We’re Looking For

    Required

  • 3–6+ years in Data Science, ML Engineering, or a full-stack data role
  • Strong Python engineering fundamentals (Pandas, NumPy, scikit-learn, async workflows)
  • Hands-on experience with LLM systems (embeddings, retrieval, fine-tuning, structured prompting, agent-style workflows)
  • Experience building and maintaining ETL pipelines from multiple SaaS systems and CSV / Excel sources
  • Experience integrating with CRM and accounting APIs (HubSpot, QuickBooks, or comparable platforms)
  • Strong SQL skills and experience designing logical data models
  • Demonstrated ability to build internal automation tools or operational scripts
  • Excellent written communication and documentation skills
  • Nice to Have

  • Experience with workflow orchestration tools (Airflow, Prefect, Make, Zapier)
  • Experience with OpenAI, Anthropic, or similar LLM ecosystems
  • Experience building retrieval systems or internal knowledge bases
  • Background in e-commerce, wholesale, or operations-heavy environments
  • What This Role Offers

  • Ownership of the entire data and AI automation ecosystem
  • A chance to build from scratch : pipelines, agents, tooling, and internal intelligence systems
  • Direct work with executive leadership and major influence on company operations
  • The ability to dramatically reduce manual workload across teams through automation
  • A high-impact role where your work is used daily across the organization
  • Create a job alert for this search

    Data Scientist • Hyderabad, Republic Of India, IN

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