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Battery Data Scientist Jobs (NOW HIRING)

Data Engineer - Battery Data Platform & AI

Cupertino, CA · On-site

$141K - $169K/yr

On Apple's Battery Engineering team, you'll build the data systems and AI interface that battery ... Think of it as giving every engineer their own personal data scientist. You'll engineer the full ...

Data Engineer

Cupertino, CA · On-site

$141K - $169K/yr

As part of our Battery Engineering group, you'll help craft creative battery solutions that deliver ... Minimum Qualifications Bachelor's in computer science, engineering, or related fields Experience ...

As part of our Battery Engineering group, you'll help craft creative battery solutions that deliver ... computer science, engineering, or related fields with minimum 5 years of relevant industry ...

BMS Data Analysis Engineer

Houston, TX · On-site

$109K - $131K/yr

Required : • Master's or PhD in Computer Science, Mathematics, Engineering, or a related field. • 2-5 years of experience in data analysis, preferably in battery systems, energy storage, or ...

New

Senior Battery Engineer

Palo Alto, CA

$122K - $168K/yr

Analyze battery performance data from flight tests and commercial operations to drive continuous ... Bachelor's degree in Chemical Engineering, Materials Science, Mechanical Engineering, Electrical ...

Design and oversee the development of intuitive user interfaces for battery data analysis, ensuring ... Data Science, Chemical Engineering, Materials Science, or a related field, or equivalent ...

Senior Battery Engineer

Palo Alto, CA · On-site

$211K - $224K/yr

Analyze battery performance data from flight tests and commercial operations to drive continuous ... Bachelor's degree in Chemical Engineering, Materials Science, Mechanical Engineering, Electrical ...

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Battery Data Scientist information

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$46K

$165K

$243.5K

How much do battery data scientist jobs pay per year?

As of Jul 8, 2026, the average yearly pay for battery data scientist in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

How does a Battery Data Scientist typically collaborate with engineers and product teams?

Battery Data Scientists work closely with engineers, product managers, and sometimes manufacturing teams to analyze and interpret data from battery systems. They frequently participate in multidisciplinary meetings to discuss findings, troubleshoot issues, and recommend optimizations based on their data analyses. Effective communication is key, as they must translate complex data insights into actionable recommendations that engineers and product teams can implement. This collaborative environment not only accelerates innovation but also provides opportunities for Battery Data Scientists to broaden their technical knowledge and contribute to product development.

What are the key skills and qualifications needed to thrive as a Battery Data Scientist, and why are they important?

To thrive as a Battery Data Scientist, you need a solid background in data analysis, machine learning, and battery technology, often supported by a degree in engineering, physics, or data science. Familiarity with programming languages like Python or R, experience with battery management systems (BMS), and knowledge of data visualization and modeling tools are highly valued. Critical thinking, problem-solving abilities, and effective communication are essential soft skills for collaborating across multidisciplinary teams and translating technical findings into actionable insights. These skills are crucial for optimizing battery performance, advancing energy storage solutions, and driving innovation in the field.

What is a Battery Data Scientist?

A Battery Data Scientist is a professional who analyzes and interprets large sets of data related to batteries, such as their performance, degradation, and efficiency. They use statistical methods, machine learning, and domain expertise to extract insights that can improve battery design, predict lifespan, and optimize charging cycles. These experts often work closely with engineers and researchers to solve problems in battery development and deployment, particularly in industries like electric vehicles and renewable energy storage.

What is the difference between Battery Data Scientist vs Battery Engineer?

AspectBattery Data Scientist

Required CredentialsDegree in Data Science, Computer Science, Electrical Engineering, or related fields; proficiency in data analysis, machine learning, and programming languages like Python or R.

Work EnvironmentPrimarily office-based, working with large datasets, modeling, and analytics tools; collaboration with R&D and engineering teams.

Employer & Industry UsageUsed in battery manufacturing companies, automotive, and energy storage industries to optimize battery performance and lifespan through data analysis.

In summary, a Battery Data Scientist focuses on analyzing data to improve battery technology, whereas a Battery Engineer is involved in designing, testing, and manufacturing batteries. Both roles require technical expertise, but their core responsibilities differ significantly.

More about Battery Data Scientist jobs
What cities are hiring for Battery Data Scientist jobs? Cities with the most Battery Data Scientist job openings:
What states have the most Battery Data Scientist jobs? States with the most job openings for Battery Data Scientist jobs include:
Data Engineer - Battery Data Platform & AI

Data Engineer - Battery Data Platform & AI

Apple

Cupertino, CA • On-site

$141K - $169K/yr

Full-time

Posted 21 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 667 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers


Job description

What if the way an entire engineering organization worked with its data could be reinvented? On Apple's Battery Engineering team, you'll build the data systems and AI interface that battery engineers across the company rely on reliable pipelines feeding one of the cleanest and largest battery datasets anywhere, and a natural language interface that's changing how engineers work with that data. You'll be building the platform the whole battery organization runs on. It's a rare chance to sharpen your data engineering craft and immerse yourself in applied AI at once.
Description
We're looking for a data engineer to build that platform across two tightly connected fronts.
First, you'll expand the Battery Data Warehouse (BDW) a mature, exceptionally clean dataset that spans the entire battery product development lifecycle: raw materials and characterization, fabrication, performance testing, simulation and modeling, qualification, manufacturing, and field telemetry. You'll build reliable pipelines that bring this data - structured, semi-structured, and unstructured - out of disparate systems owned by teams around the world. A big part of the job is technical; an equally big part is human: earning the trust of source-system owners, opening up new integration opportunities, and establishing and enforcing the SLAs that keep BDW dependable.
Second, you'll build out BARD, the natural language interface to BDW. Done well, BARD will fundamentally change how battery engineers interact with their data, not just replacing dashboards and SQL with conversation, but pairing it with on-demand, in-line charting for real-time analysis and new ways to explore data. Think of it as giving every engineer their own personal data scientist. You'll engineer the full agentic stack: our custom MCP server, agentic search, domain knowledge, tool design, evals, and the end-to-end user experience.
The role combines data engineering and AI engineering work. This role calls for someone who's both highly self-directed and an exceptional collaborator. You'll take real ownership and drive projects forward, while staying closely aligned with the team and our broader direction.
Minimum Qualifications
BS in Computer Science, Engineering, or a related field
Experience with Python, SQL, and at least one other high-level programming language
Experience building production data pipelines (ETL/ELT)
Preferred Qualifications
MS in Computer Science, Engineering, or a related field with 10+ years of relevant industry experience
Strong database fundamentals: data modeling, schema design, indexing, normalization, ACID, and OLTP vs. OLAP
Hands-on database development (DML, DDL, materialized views, stored procedures); Snowflake (streams, tasks, dynamic tables) a plus
Hands-on experience with orchestration (e.g., Airflow), batch/stream processing, and cloud platforms (e.g., AWS)
Deep curiosity about AI and hands-on experience applying it - at work or in personal projects. You keep up with the latest tools, use AI daily (including for coding), and have strong intuition for context engineering, tokenization, embeddings, and evals, as well as a clear sense of where AI excels and where it doesn't (e.g., generating new code vs. maintaining complex existing code)
Experience with LLM and MCP server development
Strong communication and relationship-building skills, with the ability to align stakeholders and drive integrations across organizational boundaries
Familiarity with batteries or other deep-tech / hardware engineering domains

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976