Battery Analytics Data Scientist

Key Skills

Java Programming, Python Programming, Database, Framework, SQL, Git, AWS, Apache Hadoop, Machine learning techniques, Data science techniques, Jenkins, JIRA, Data Mining, Data Visualization, Deep Learning, Keras software library, MATLAB Programming, NoSQL, PyTorch, TensorFlow, Apache Hive, R Programming, MySQL, Statistics, ggplot, SPARK Programming, Mathematics, CDASH, Server architectures, FastAPI

Job Description

As a world leader in developing and producing the most advanced engineering technologies, we improve lives and further human achievements worldwide, while also protecting the climate - all thanks to our employees.

With us, you can do something significant that benefits society and human progress

Your new role – challenging and future-oriented

The position presents a unique opportunity to improve and transform the current state-of-the-art Battery Energy Storage Systems (BESS) Digitalization and Analytics. As a part of our BESS tools team, you will, together with dedicated international colleagues, get the chance to work with and build up a world-class BESS Digitalization R&D group. We are looking for flexibility, curiosity, and eagerness to learn in the candidate. You will get the opportunity to have a tangible impact on our success story. This position requires a creative and analytical mindset with a strong understanding of data analysis, signal processing, pattern recognition, and machine learning. The candidates will have the opportunity to develop their skills and knowledge on two highly demanded topics: data analysis and battery energy storage technology.

• You should be passionate to solve battery analytics problems using data-based approaches.
• Work with the battery energy storage system (BESS) stakeholders to identify the improvement areas in the currently available techniques.
• Explore different feature extraction methodologies and performance metrics of batteries under different battery usage and ageing conditions for discovering insights.
• Develop new monitoring indicators and their associated algorithms using time series prediction and anomaly detection techniques, with the final goal to deploy them using cloud-based tools.
• Utilize different supervised/unsupervised machine learning techniques to build predictive models for prognostics applications, predictive maintenance, which includes battery quality metrics, performance metrics of power/energy and remaining useful life/ state of health estimation.
• Run cloud-based data models to improve battery power and energy estimation based on current, voltage and temperature data points across various drive cycles and geographies.
• Accelerate battery analytics platform development and model management using cloud-native solutions.

We don’t need superheroes, just super minds

• BS/BE/BTech, or MS/MCA degree in Data Science / Statistics / Computer Science / Information Systems/Electrical engineering/Mechanical engineering.
• A Master’s or PhD is preferred (Statistics /Computer Science / Machine Learning, etc). Proficiency with data mining, mathematics, and statistical analysis with significant hands-on experience in AI / Data Science.
• You need to be an engineering graduate with at least 6-8 years of experience in design and development.
• You should have ability to work as an individual contributor (IC role).
• You must have Customer focus and effective stakeholder management skills.

Expected Skills:

• Knowledge of data wrangling, data cleaning and data visualization techniques.
• Knowledge in signal processing, statistics, time series forecasting, probabilistic machine learning and deep learning frameworks.
• Programming skills in Python/R/MATLAB etc. and demonstrable skills in standard data visualization libraries like matplotlib, seaborn, bokeh, plotly, ggplot2 etc. and deep learning frameworks including Tensorflow, Pytorch, Keras, CNTK etc.
• Demonstrable history of production-ready algorithm/model development and hyperparameter tuning.
• Must have good understanding of different Cloud Systems, knowledge of AZURE/AWS Cloud and services is must to have.
• Experience working with and creating data architectures.
• Has worked in agile projects with tools such as Git, Leankit, Jenkins and Jira
• Good knowledge of querying SQL & No SQL databases.
• Experience in developing & deploying the end-to-end data science pipeline into production.
• Good analytical, debugging and tracing skills. Should be well-versed with clean code principles (SOLID, DRY, KISS). Exposure to secure coding is beneficial.

Good if you must have:

• Knowledge in the battery electrification domain and a good understanding of the physical sciences in lithium-ion batteries.
• Basic knowledge of FastAPI, DASH, Streamlit, Gradio would be beneficial.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc.

Other expected traits:

• Creativity and analytical mindset
• Quick learner and detailed oriented
• Excellent communication skills with an ability to present articulated solutions to senior management and staff levels.