Data Science Platform Lead

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Syngenta Group is a leading science-based agritech company; dedicated to bringing plant potential to life. Each of our 48,000 employees in more than 100 countries work together to solve one of humanity’s most pressing challenges: growing more food with fewer resources. A diverse workforce and an inclusive workplace environment are enablers of our ambition to be the most collaborative and trusted team in agriculture. Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. Join us and help shape the future of agriculture.

Syngenta’s 25 billion$ business is in need for an experienced, pragmatic Data science platform engineer to join our Data & Analytics team, support Syngenta Group. For this role, we are offering a permanent contract. The position is based in our office in Guyancourt (78). 

• The mission is building a scalable data foundation for a rapid growing data savy Agriculture company. Therefore we are looking for A-players who are ready for the challenge of creating a Data Science Platform based on mostly AWS services (Sagemaker, Lambda, Glue, Python, Jupyter notebooks, Stepfunction etc… ).
• The Data science platform engineer (large focus on machine learning) will be a key contributor to the data science Platform Development and Operations, in line with functional and cross functional needs.
• This engineer is a co-owner of the data science platform and manages it in order to serve current and future business needs. In this respect he/she is accountable to create, maintain and deploy a platform roadmap aligned with prioritized business requirements and Data & Analytics strategies, and monitor this platform.
• The Platform lead supported by the data science platform engineers must ensure his platform is flexible and scalable to serve both short- and long-term purposes. Consequently, the data science platform engineer has to help dimension the platform adequately at all times in order to guarantee a cost-efficient service, drive continuous improvement, and proactive service management.
• The Data science platform engineer collaborate with other IT and digital functions to ensure comprehensive and suitable integration of his/her platform in the overall IT landscape.

Accountabilities:

• To contribute evaluate, select, configure and deploy the tools operating within the platform area’s remit, when appropriate own these tools on behalf of business user’s community.
• Contribute to establish and deploy a roadmap for his/her platform area and drive its adoption.
• To manage business stakeholders / data scientist community having a dependency with the platform content and/or usage, and educate workforces about this platform usage.
• To coordinate platform content exploitation, mitigate conflicting interests and risks associated to the platform, and create and scale associated services.
• To establish clear accountabilities and ownership of content and tools being part of the platform landscape.
• You will help lay the foundation that allows the Data Scientist to accelerate and therefore more effectively scale its impact.
• To monitor and optimize platform usage.
• To promote effective sharing of best practices across the organization. Lead, direct, coach and develop stakeholder community ensuring platforms adoption to meet business needs.
• To define and deploy the platform necessary support model that guarantee meeting operational requirements.
• To govern necessary changes modifying platform landscape, content and usage.

Experience, competences and soft skills required for the job:

• Expertise of cloud-based data science platform management, ideally AWS Sagemaker (AWS certifications, Sagemaker, cloud Architecture etc…, data science is a plus).
• Can showcase strong coding experience (e.g. Python, SQL,R,…). 
• Track record of managing 3rd party, external suppliers, and internal/augmented delivery teams.
• Experience with Agile methodology (ideally LeSS). and DevOps delivery concepts.
• Strong experience in data scientist stakeholder management.
• Demonstrated ability to enable delivery of visualization and analytics for business outcomes and an extensive knowledge of the tools available on the market.
• Awareness of current best practices in data science domain.
• Ability to articulate vision and mission and goals that inspires and motivate teams to action.
• Ability to gather right people together to solve problems from any place within and or outside the organization.
• Ability to transform business requirement into expected platform outcome.
• Excellence in network building, stakeholder management and influencing skills.
• Fluency in English and French.