Principal Battery Research Data Scientist
Posted on 2/5/2024

1,001-5,000 employees

Global provider of energy storage products, services, and AI-enabled cloud
Company Overview
Fluence, a global leader in energy storage products, services, and cloud-based software, is a compelling place to work due to its commitment to driving the clean energy transition across 40 markets worldwide. The company's robust sustainability framework, advanced AI-enabled SaaS products, and modular, scalable energy storage solutions demonstrate its technical prowess and industry leadership. Fluence's focus on creating resilient and sustainable electric grids, coupled with its ability to deliver turnkey solutions and optimize storage and renewable assets, positions it as a competitive player in the renewable energy sector.
AI & Machine Learning
Data & Analytics

Company Stage

Series C

Total Funding





Arlington, Virginia

Growth & Insights

6 month growth


1 year growth


2 year growth

Houston, TX, USA
Experience Level
Desired Skills
Power BI
Data Science
Data Structures & Algorithms
Data Analysis
Data & Analytics
  • Required Experience and Skills
  • PhD or Master's in computer science (or related fields) and 3-5 years of experience in Artificial Intelligence (AI) and Machine Learning (ML), Data Science, Data Engineering, Data Mining, ML Operations (MLOps), and related fields
  • Working knowledge of statistics, time series forecasting, feature engineering, regression, classification, clustering, outlier detection, reinforcement learning, few shot learning, multidimensional Kalman filtering, extended Kalman filters, optimization, and causal inference
  • Staying up to date with novel AI algorithms and tools and implement them 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
  • 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
  • Strong written and oral communication and ability to document technical findings
  • Willingness and desire to lead technical teams and product development team
  • Developing test plans and QA procedures for algorithm/code verification and validation
  • Desired Experience and Skills
  • PhD or Master's in Materials Science, Chemical Engineering, Mechanical Engineering, Power Systems or related fields with deep understanding of lithium-ion electrochemistry effects as applies to simulation and modeling with track records of peer-reviewed publications/patents
  • Peer-reviewed record of publications in machine learning and artificial intelligence peer-reviewed journals and conferences/patents
  • Experience and knowledge in Battery System State (State of Charge (SOC), State of Health (SOH), State of Functionality (SOF), State of Power (SOP), SOx, Capacity) estimation, battery safety, internal cell temperature and thermal gradients, internal resistance, balancing, 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
  • Ability to develop and verify physics-based and empirical battery models to support algorithm needs
  • Validation of the algorithms in Model-in-the-loop (MIL) and Hardware-in-the-loop (HIL) settings and/or a lab
  • Experience with Tableau, SQL, R, Perl, Scala, JMP, Octave, Matlab, Simulink, C++, Julia, and Go
  • Familiarity with data acquisition systems
  • Experience with firmware and embedded systems for Battery Management Systems (BMS)
  • 3 to 5 years of industrial experience in battery systems
  • Leads 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 minimal guidance
  • Interprets results and develops insights into formulated problems within the business/customer context
  • Acquires and uses broad knowledge of innovative battery state estimation/ prediction/ fault detection methods, algorithms, and tools from the scientific literature and applies his/ her own analysis of scalability and applicability to the formulated problem
  • Helps in developing long-term battery analytics strategy and roadmap
  • Effectively collaborates and communicates with the team members, product owners, product managers, as well as marketing and sales teams, customers, and leadership