Sr Data Scientist (AI, RAG, Agentic AI, LLM) – Bay Area, CA & Austin, TX

Tech Mirrors; San Francisco (CA); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Tech Mirrors is seeking a Senior Data Scientist to leverage applied analytics and GenAI‑aware capabilities across business units. You will work with data engineers to build scalable features and deploy models in production.

The role emphasizes collaboration with product teams, experiments, and delivering insights through dashboards and storytelling with data.

Qualifications

• Strong DS fundamentals: statistics, probability, hypothesis testing.
• Proficient in Python (pandas, NUMPY, scikit‑learn).
• Advanced SQL for large analytical datasets.
• Experience deploying ML models in production.
• Exposure to GenAI / LLMs (prompting, RAG analytics).
• Data visualization with Tableau, Power BI or Looker.

Responsibilities

• Perform advanced data analysis to uncover trends and drivers.
• Build and deploy statistical and ML models (classification, regression, clustering).
• Partner with Data Engineering to productionize features and datasets.
• Apply GenAI/LLMs for analytics use cases (insight generation, summarization, recommendations).
• Design experiments and measure impact (A/B testing, KPI tracking).
• Communicate insights to business and product stakeholders.

Skills

Data science fundamentals

Python

SQL

Production ML models

GenAI / LLMs

Data visualization

Tools

Tableau

Power BI

Looker

Snowflake

BigQuery

Job description

SENIOR DATA SCIENTIST (APPLIED / GENAI‑AWARE)

Role:Senior Data Scientist

Experience:6–10 years

Location:Bay Area / Austin

Key Responsibilities

• Perform advanced data analysisto uncover trends, patterns, and drivers
• Build and deploy statistical & ML models(classification, regression, clustering)
• Partner with Data Engineering to productionize features and datasets
• Apply GenAI / LLMsfor analytics use cases (insight generation, summarization, recommendations)
• Design experiments and measure impact (A/B testing, KPI tracking)
• Communicate insights to business & product stakeholders

Required Skills

• Strong Data Science fundamentals(statistics, probability, hypothesis testing)
• Python(pandas, NUMPY, scikit‑learn)
• SQL (advanced)for large analytical datasets
• Experience with ML models in production
• Exposure to GenAI / LLMs(prompting, RAG‑enabled analytics)
• Data visualization (Tableau / Power BI / Looker)

Nice to Have

• Feature engineering for ML systems
• Vector embeddings & semantic search
• Snowflake / BigQuery analytics
• Domain knowledge (Sales, Ops, CRM, Supply Chain)