{"id":4013613,"url":"https://alion.io/job/lyten-staff-battery-data-scientist","title":"Staff Battery Data Scientist","company":{"id":58667,"name":"Lyten","domain":"lyten.com","url":"https://alion.io/company/lyten","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Jose, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":141000,"max":212000,"currency":"USD","period":"year","gross":null,"usd_annual":212000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GitHub","optional":false},{"name":"LLM","optional":false},{"name":"MLFlow","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SciPy","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Statistical Process Control","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series","optional":false}],"status":"live","first_seen_at":"2026-11-10T09:52:30Z","employer_posted_date":null,"last_verified_at":"2026-11-10T09:52:30Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Lyten, Inc. is hiring a Staff Battery Data Scientist to turn lithium-sulfur cell, process, and quality data into insights that improve performance and production yield. The role works across R&D, process engineering, quality, and manufacturing to develop analytical systems, predictive models, and repeatable approaches to learning.\n\nResponsibilities\nIdentify failure drivers in cell, process, and quality data, and turn them into a prioritized list of next steps for engineering and operations\nLead lithium-sulfur analytics, including cell-to-cell variation, capacity fade, formation behavior, and early-life prediction of long-term performance\nClean and analyze high-volume time series data from cyclers, formation equipment, and manufacturing tools, and link it with cell-level quality data to find root causes\nBuild, validate, and deploy ML models for performance prediction, anomaly detection, and process optimization, and know when a simpler statistical method is the better choice\nDesign DOE, SPC, and statistical testing that give engineers actionable decisions, and communicate findings, including uncertainty, to technical and executive audiences\nUse AI and LLM tooling to automate recurring analyses and build a searchable knowledge base so learnings persist beyond individuals\nMentor junior team members and set standards for analytical rigor and reproducibility\n\nSkills\nBS/MS/PhD in data science, electrochemistry, materials science, chemical engineering, computer science, or equivalent experience\nMinimum of 8 years in data science or analytics, including 4+ years working with battery, electrochemical, or comparable high-volume manufacturing data\nStrong Python and SQL skills, with proficiency in the scientific Python and ML stack (pandas, SciPy, scikit-learn, and PyTorch or TensorFlow)\nDemonstrated experience with large-scale time series analysis of instrument or tool data, and with SPC, DOE, and root cause analysis in a manufacturing setting\nTrack record of taking ML models from prototype to production, using modern data platforms (e.g., Databricks, Snowflake) and version control (GitHub)\nHands-on experience applying LLMs or agentic tools (e.g., RAG, MCP integrations) to automate analysis or knowledge retrieval\nAdaptable, first-principles thinker who can separate signal from noise, find root causes, and creatively solve problems for a new battery chemistry\nExperience with lithium-sulfur or other next-generation battery chemistries\nFamiliarity with cell formation, cycling, EIS, and BMS data\nExperience building or supporting data pipelines (SQL/Python-based ETL/ELT, Spark, orchestration frameworks) and working with MES systems and their data outputs\nExperience with MLflow, Unity Catalog, or similar model and data governance tooling\nExperience with Bayesian methods or survival and reliability modeling\n\nBenefits\nTier based bonus and equity\nHealthcare, dental, and vision\nCorporate discounts\nPaid holidays, PTO, and sick time\n401K\nEmployee relocation plan (if applicable)\nA mission that matters: Contribute directly to solving complex challenges in energy, mobility, and materials innovation.\nCutting-edge innovation: Work on technologies at the intersection of materials science, energy storage, and advanced manufacturing that strengthen energy security and local supply chains.\nExtraordinary people: Join a team of talented, friendly, and down-to-earth innovators who support, challenge, and inspire one another every day.\nTeamwork and culture: Experience a workplace built on trust, respect, and shared success — where collaboration fuels breakthroughs and everyone’s ideas are heard.\nGlobal impact: Help scale new materials and energy solutions that reinforce industrial resilience across the U.S. and Europe.\nCareer growth: Be part of a fast-moving company entering a commercial growth phase, with opportunities to lead, learn, and make your mark.\nPurpose-driven values: Thrive in an environment that celebrates ingenuity, optimism, and meaningful progress — together.\n\nCompany Overview\nLyten is a supermaterial applications company that develops, sources, and manufactures low-carbon footprint products. It was founded in 2015, and is headquartered in San Jose, California, USA, with a workforce of 501-1000 employees. Its website is http://www.lyten.com.\n\nCompany H1B Sponsorship\nLyten has a track record of offering H1B sponsorships, with 6 in 2026, 5 in 2025, 5 in 2024, 4 in 2023, 2 in 2022, 1 in 2021. 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