Lesaffre
Marcq-en-Baroeul, Lille 19/03/2023Partager cette annonce: Postuler
Lesaffre recherche …
A key global player in fermentation for more than a century, Lesaffre, with a 2, 2 billion euro turnover, and established on all continents, counts 10, 700 employees and more than 85 nationalities. On the strength of this experience and diversity, we work with customers, partners and researchers to find ever more relevant answers to the needs of food, health, naturalness and respect for our environment. Thus, every day, we explore and reveal the infinite potential of microorganisms.
To nourish 10 billion people, in a healthy way, in 2050 by making the most of our planet's resources is a major and unprecedented issue. We believe that fermentation is one of the most promising answers to this challenge.
In the context of the launch of an ambitious program to foster the use and valorization of data across the company, Lesaffre International seeks to accelerate and structure its data delivery capabilities and competences.
Reporting to the Head of Data Science, the Data Scientist will join a team with several outstanding profiles (data scientists, Data engineers). The data Scientisit is a scientific data expert playing a key role in the data use cases' framing, the statistical & AI modeling, and the development of Lesaffre Group data use cases. The Data Scientist will BE part of features team that deliver innovative data use cases with various business domains and geographies across the company, such as :
- Factory 4.0 data projects to optimize the production processes in the factories of Lesaffre, and involving factory sensor data
- Data projects linked to state-of-art R&D regarding the expertise domains of Lesaffre (e.g., complex yeast strain screening, AI for genomics engineering, fermentation modulization etc.)
- All relevant other data projects to optimize the group operations (supply chain optimization, demand sensing, etc.)
Main responsibilities
The Data Scientist designs the scientific methodology to solve business problems
Translate business challenges into scientific problems
Build efficient statistical or AI models
Communicate in a pedagogical way to Lesaffre group stakeholders
The Data Scientist supports the data use case framing
Make preliminary analysis to assess the data quality
Estimate the feasibility and the performance of a data-driven approach
List the data prerequisites to start a data use case
The Data Scientist develops data use cases and supports on the monitoring in production
Implement and structure the end-to-end data treatments and pipeline
Package AI models training and predict components
Define specific metrics to monitor the model performance in production
Experience
Master's degree or PhD in engineering, science, computer science, machine learning, applied statistics, biostatistics, physics or mathematics
At least 3 years of experience on relevant roles (data scientist, machine learning engineer, senior data analyst, R&D engineer, biostatistician).
Hands-on experience with implementing data and AI models
Previous experience with technical/research/industrial data would BE ideal
Technical skills
Machine learning and scientific methodology :
Experience in finding data science solutions to business problems
Good knowledge of statistical and data science concepts (e.g, model evaluation, overfitting, parameter tuning, null imputation)
Experience in data & AI modelling including both classification, regression and clustering problems in python using scikit-learn (e.g, linear models, random forests, gradient boosting, svm, knn, etc.)
Ideally at least one strong scientific expertise (e.g, interpretability, time series forecasting, genomics, image recognition, etc.)
Data analytics, processing and visualization :
Strong programming experience with data-related packages in Python (e.g., numpy, scipy, pandas, scikit-learn)
Additional programming experience in R would BE a plus
Experience in data treatment (e.g, filter, aggregate, merge, etc.)
Experience in data visualization (e.g., seaborn, matplotlib, plotly, dash, Streamlit, PowerBi, Tableau)
Experience with data quality analysis (e.g., null values and outlier's detection)
Data use case development and monitoring :
Programming experience in Python using virtual environment, typing, debugging, logging and testing
Experience with collaborative tools (e.g., git)
Experience in data storage and data modeling
Experience with at least one SQL and one NoSQL database (e.g., MySQL, MongoDB, CassandraDB)
Ideally experience in deployment and monitoring of data use case and/or AI model in production on Cloud (e.g., AWS, Azure, OVH, GCP)
Other skills
Strong science skills
Business and innovation oriented
good communication skills
Demonstrated ability to deliver in autonomy scientific data and ML methodology that answer to business needs
Full English proficiency. French proficiency is a plus.
Postuler
A key global player in fermentation for more than a century, Lesaffre, with a 2, 2 billion euro turnover, and established on all continents, counts 10, 700 employees and more than 85 nationalities. On the strength of this experience and diversity, we work with customers, partners and researchers to find ever more relevant answers to the needs of food, health, naturalness and respect for our environment. Thus, every day, we explore and reveal the infinite potential of microorganisms.
To nourish 10 billion people, in a healthy way, in 2050 by making the most of our planet's resources is a major and unprecedented issue. We believe that fermentation is one of the most promising answers to this challenge.
In the context of the launch of an ambitious program to foster the use and valorization of data across the company, Lesaffre International seeks to accelerate and structure its data delivery capabilities and competences.
Reporting to the Head of Data Science, the Data Scientist will join a team with several outstanding profiles (data scientists, Data engineers). The data Scientisit is a scientific data expert playing a key role in the data use cases' framing, the statistical & AI modeling, and the development of Lesaffre Group data use cases. The Data Scientist will BE part of features team that deliver innovative data use cases with various business domains and geographies across the company, such as :
- Factory 4.0 data projects to optimize the production processes in the factories of Lesaffre, and involving factory sensor data
- Data projects linked to state-of-art R&D regarding the expertise domains of Lesaffre (e.g., complex yeast strain screening, AI for genomics engineering, fermentation modulization etc.)
- All relevant other data projects to optimize the group operations (supply chain optimization, demand sensing, etc.)
Main responsibilities
The Data Scientist designs the scientific methodology to solve business problems
Translate business challenges into scientific problems
Build efficient statistical or AI models
Communicate in a pedagogical way to Lesaffre group stakeholders
The Data Scientist supports the data use case framing
Make preliminary analysis to assess the data quality
Estimate the feasibility and the performance of a data-driven approach
List the data prerequisites to start a data use case
The Data Scientist develops data use cases and supports on the monitoring in production
Implement and structure the end-to-end data treatments and pipeline
Package AI models training and predict components
Define specific metrics to monitor the model performance in production
Experience
Master's degree or PhD in engineering, science, computer science, machine learning, applied statistics, biostatistics, physics or mathematics
At least 3 years of experience on relevant roles (data scientist, machine learning engineer, senior data analyst, R&D engineer, biostatistician).
Hands-on experience with implementing data and AI models
Previous experience with technical/research/industrial data would BE ideal
Technical skills
Machine learning and scientific methodology :
Experience in finding data science solutions to business problems
Good knowledge of statistical and data science concepts (e.g, model evaluation, overfitting, parameter tuning, null imputation)
Experience in data & AI modelling including both classification, regression and clustering problems in python using scikit-learn (e.g, linear models, random forests, gradient boosting, svm, knn, etc.)
Ideally at least one strong scientific expertise (e.g, interpretability, time series forecasting, genomics, image recognition, etc.)
Data analytics, processing and visualization :
Strong programming experience with data-related packages in Python (e.g., numpy, scipy, pandas, scikit-learn)
Additional programming experience in R would BE a plus
Experience in data treatment (e.g, filter, aggregate, merge, etc.)
Experience in data visualization (e.g., seaborn, matplotlib, plotly, dash, Streamlit, PowerBi, Tableau)
Experience with data quality analysis (e.g., null values and outlier's detection)
Data use case development and monitoring :
Programming experience in Python using virtual environment, typing, debugging, logging and testing
Experience with collaborative tools (e.g., git)
Experience in data storage and data modeling
Experience with at least one SQL and one NoSQL database (e.g., MySQL, MongoDB, CassandraDB)
Ideally experience in deployment and monitoring of data use case and/or AI model in production on Cloud (e.g., AWS, Azure, OVH, GCP)
Other skills
Strong science skills
Business and innovation oriented
good communication skills
Demonstrated ability to deliver in autonomy scientific data and ML methodology that answer to business needs
Full English proficiency. French proficiency is a plus.
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