Technical Data Analyst II

RESPONSIBILITIES

A client with Kforce is seeking a Technical Data Analyst II to join their team in Mountain View, CA.

Summary

We're looking for an AI Full Stack Scientist - a rare hybrid who can design ML models, build the agentic infrastructure that powers them, and ship end-to-end AI-powered products with polished user-facing experiences. This role sits at the intersection of applied machine learning, platform engineering, and product development. You won't just build models and hand them off. You'll own the full lifecycle - from research and experimentation to production deployment to the interface a customer or internal user actually touches.

Duties

• Design, train, and deploy ML models for personalization, classification, ranking, and recommendation at scale (millions of records)
• Build and fine-tune NLP/embedding models (SBERT, Jina, transformer architectures) for semantic understanding and search
• Design and run rigorous A/B experiments - hypothesis formation, power analysis, metric selection, causal inference
• Evaluate and integrate emerging GenAI capabilities (LLMs, RAG pipelines, multi-modal models) where they create real value vs. where classical ML is the right tool
• Architect and build agentic AI systems - tool-using agents, MCP servers, multi-step reasoning workflows
• Design knowledge governance systems - schema design, semantic layers, async sync pipelines
• Build ML platform tooling that accelerates experiment velocity for the broader team (model selection, parallel execution, automated provisioning)
• Own the infrastructure decisions that are hard to reverse: interfaces, data contracts, governance models
• Build end-to-end AI-powered applications - from model inference backend to production frontend (React/Next.js, TypeScript)
• Create interactive dashboards, data tools, and internal products that make AI outputs accessible to non-technical stakeholders

REQUIREMENTS:

• BS (MS a plus) in a quantitative field - Statistics, Economics, Computer Science, Engineering, or equivalent experience
• Experience in applied ML/AI with models deployed to production at scale
• Strong Python - ML frameworks (PyTorch/TensorFlow), data processing (PySpark, Pandas), API development (FastAPI/Flask)
• NLP & Embeddings - hands-on experience with transformer models, semantic search, fine-tuning, and retrieval-augmented generation
• Experimentation rigor - A/B testing design, statistical significance, causal reasoning
• Distributed computing - experience processing millions of records (Spark, GPU clusters, autoscaling)
• SQL mastery - complex queries, ETL pipelines, data modeling
• Frontend capability - React or Next.js, TypeScript, ability to build production-quality UIs (not just notebooks)
• Agentic AI systems - experience building or architecting tool-using agents, MCP servers, or multi-step AI workflows

Nice-to-Have:

• Experience with marketing personalization, recommendation systems, or customer segmentation
• Familiarity with MLOps tooling (MLflow, Weights & Biases, model registries)
• Experience building developer tools or internal platforms adopted by other teams
• Contributions to semantic layer or data governance systems
• Knowledge of real-time serving infrastructure (streaming, feature stores, low-latency inference)

The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.

Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law. This job is not eligible for bonuses, incentives or commissions. Kforce is an Equal Opportunity/Affirmative Action Employer.

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