Main Responsibilities :
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.
Prerequisites :
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.
Databricks notebooks (Python/SQL)
Experience in Knowledge Graph a plus
Strong proficiency in pandas and numpy for exploration, feature engineering and analytical workflows
English & French are both mandatory
Skills Required
- 8–11 years of professional experience
- Master’s degree or PhD in Data Science, Applied Mathematics, Statistics, or a related field
- Experience working with large-scale datasets in an industrial environment
- Strong fundamentals in linear algebra, calculus, probability, and statistics
- Understanding of distributed systems, data partitioning, and parallel processing
- Hands-on experience with Databricks for data exploration, analysis, feature engineering, and model training
- Strong proficiency in Apache Spark, including DataFrames, SQL, and MLlib concepts
- Hands-on experience with distributed model training using PyTorch or TensorFlow
- Experience with Databricks notebooks using Python and SQL
- Strong proficiency in pandas and NumPy
- Fluency in both English and French
- Experience with knowledge graphs
What We Do
Verkor is a French industrial company based in Grenoble. With the backing of EIT InnoEnergy, Groupe IDEC, Schneider Electric, Capgemini, Renault Group, EQT Ventures, Arkema, Tokai COBEX, FMET managed by Demeter, Sibanye-Stillwater and Plastic Omnium, Verkor will ramp up low-carbon battery manufacturing in France and Europe to meet the growing demand for electric vehicles — and electric mobility as a whole — and stationary storage in Europe. Verkor is developing an enticing business model based on agility, sustainability and governance that is attracting the best talents from around the world. Its strong and agile team continues to grow as new challenges arise. Verkor is leading a unifying project that brings together the best partners for establishing the entire value chain in Europe and ensuring the optimal use of skills and resources. Verkor will draw on these strengths to open its entirely digital 4.0 pilot line in 2022. A model of excellence, competitiveness and resource efficiency, this innovation will be integrated into the gigafactory due for construction in 2024. Please apply today with an English CV on our website: https://www.verkor.com/en/join-our-team
