Staff Battery Data Scientist - Lithium-Sulfur Analytics

Lyten, Inc.; San Jose (CA); On-site; USD 141,000 - 212,000; Full time

Benefits offered by this job

Tier-based bonus

Equity

Healthcare

Dental

Vision

401K

Paid holidays

PTO

Sick time

Relocation assistance

Job summary

Lyten, Inc. is seeking a Staff Battery Data Scientist in San Jose to turn cell, process, and quality data into actionable insights.

You will lead analytics across R&D, process engineering, quality, and manufacturing, building scalable analytical systems and ML models to improve lithium-sulfur battery performance. The role requires 8+ years in data science with 4+ years in battery analytics, strong Python/SQL, and experience with Databricks, Snowflake, and LLM-based automation.

Qualifications

• 8+ years in data science or analytics, 4+ years with battery data analytics.
• Strong Python and SQL with ML stack proficiency.
• Experience with large-scale time series data and DOE/SPC.
• Experience deploying ML models to production and using Databricks/Snowflake.
• Experience with LLMs to automate analyses and knowledge retrieval.

Responsibilities

• Identify failure drivers in cell, process, and quality data.
• Lead lithium-sulfur analytics: cell-to-cell variation and formation behavior.
• Clean and analyze high-volume time series data from cyclers and tools.
• Build, validate, and deploy ML models for performance prediction.
• Design DOE, SPC, and statistical testing for actionable decisions.
• Use AI/LLMs to automate recurring analyses and build a knowledge base.
• Mentor junior team members and set analytical standards.

Skills

Python programming

SQL

Time series analysis

LLMs / agentic tools

ML deployment

Root cause analysis

Education

BS/MS/PhD in data science or related field

Tools

Databricks

Snowflake

GitHub

MLflow

Unity Catalog

Spark

Job description

Lyten, Inc. is seeking a Staff Battery Data Scientist in San Jose to turn cell, process, and quality data into actionable insights.

You will lead analytics across R&D, process engineering, quality, and manufacturing, building scalable analytical systems and ML models to improve lithium-sulfur battery performance. The role requires 8+ years in data science with 4+ years in battery analytics, strong Python/SQL, and experience with Databricks, Snowflake, and LLM-based automation.