
Battery Data Scientist
23 hours ago
**Responsibilities**
- Acts as one of the battery data scientists in the team to meet immediate and long-term battery data analysis requests.
- Helps the team in agile development, test, and validate state-of-the-art estimation, prediction, and statistical inference algorithms in battery systems.
- Contributes to data pipeline requirements of energy storage systems.
- Applies (or develops if necessary) pipelines and tools to efficiently collect, clean, and prepare massive volumes of data for analysis with mínimal guidance.
- Uses coding and data analysis to derive data-driven decisions regarding battery systems.
- Effectively collaborates and communicates with the team members.
**Required Experience and Skills**
- Bachelor's or Master’s in computer science (or related fields/experience) with/or background/passion in Data Science, Statistics, Data Engineering, Data Mining, ML Operations (MLOps), and related fields.
- Fast learning and implementing new algorithms whenever required.
- Programming fluency in Python (and especially data science/visualization related packages).
- Working knowledge of AWS and ML platforms, Snowflake, and Power BI Dashboard.
- Working in agile software development cycles and version control tools such as Jira and Github.
- Strong problem-solving skills, with the ability to combine theory with empirical observation, especially with statistical nature.
- Interacting effectively and in an open, ethical, and trustworthy manner with internal and external stakeholders.
- Staying proactive, self‐motivated, persistent, hands‐on, goal
- oriented, and team-oriented, and work in a fast-paced, US-based, and diverse environment.
**Desired Experience and Skills**
- Experience with Tableau, SQL, R, Perl, Scala, JMP, Octave, Matlab, Simulink, C++, Julia, and Go.
- Familiarity with data acquisition systems.
- 3 to 5 years of industrial experience.
- Master’s in Materials Science, Chemical Engineering, Electrical and Computer Engineering, Mechanical Engineering, Power Systems or related fields with deep understanding of lithium-ion electrochemistry effects as applies to simulation and modeling.
- Experience and knowledge in Battery System State (State of Charge (SOC), State of Health (SOH), State of Balance (SOB), State of Energy (SOE), SOx, Capacity) estimation, battery safety, internal cell temperature and thermal gradients, internal resistance, balancing, Round Trip Efficiency (RTE), accelerated testing, open circuit voltage (OCV) prediction with hysteresis, Randles equivalent circuits, single particle models, Ficks law of diffusion, age modeling, and battery life degradation algorithms.
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