Senior Data Scientist

France·GrenobleCDI / Permanent positionsenior

Data ScientistData

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Overview

Verkor is a French industrial company aiming to pioneer low-carbon battery manufacturing in France. With the backing of prominent industrial companies such as Renault Group,

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Data ScientistData

Verkor is a French industrial company aiming to pioneer low-carbon battery manufacturing in France. With the backing of prominent industrial companies such as Renault Group, Plastic Omnium and Schneider Electric, Verkor intends to electrify the future of European mobility.

With over 1100 experts from 53 different countries, our endeavor is to unite exceptional global talent to bring this ambitious and innovative project to life. Our strong and agile international team continues to grow and adapt to new challenges. Based in Grenoble and Dunkirk (France), we have started operations our Verkor Innovation Centre (R&D centre and 4.0 pilot line) which is now fully running and operational.

We now focus on enabling the successful start of production of our Gigafactory in Dunkirk (France). With this facility, our ambition is to ramp-up mass production of low carbon lithium ion batteries to facilitate the decarbonization of European mobility.

The senior data scientist is responsible for turning data into insights, predictions and decision-support models that help the business reduce uncertainty, improve performance and scale decision making. As senior, he/she is responsible to derive KPI’s aligned to business strategy, focus on translating the business problems, into analytical questions and build data driven solutions.

Turns business questions into analytical and data science problems

Defines success metrics and evaluation criteria aligned with business outcomes

Analyze and explore structures and unstructured data to identify patterns, trends and anomalies

Build production grade automation workflows

Assess data quality, completeness, bias and limitations

Identify additional data sources needed to improve analysis or models

Perform data transformation for modelling purposes

Model development and validation

Interpret model results and analytical findings in business terms

Communicate findings clearly to non-technical stakeholders

Document assumptions, limitations and risks of the model
Works with operators and production/quality technicians to understand objectives, constraints and decision needs
Work with data engineers /Digital team to operationalize data preparation when needed.
Works with data scientists and CAE experts to understand the value of the project and how it links with the roadmap.

8 - 11 yrs of Experience

Masters or PhD in Data science/ Applied mathematics/Statistics

Experience working with large-scale data sets in an industrial environment

Strong fundamentals of linear algebra, Calculus, probability and statistics.

Solid understanding of distributed systems concepts, data partitioning and parallel processing

Hand-on experience using databricks for data exploration, analysis, feature engineering and model training

Strong proficiency in Apache spark (dataframes, SQL, ML lib concepts), for large scale data processing, with hands-on experience in distributed model training using Pytorch or tensor flow.