August 29, 2022
Apply Now
Paris (75), France
August 29, 2022
Apply NowJob description
Context:
Pernod-Ricard is looking for Machine Learning Engineer to join our Digital Transformation team, reporting to the Global Data, Design & Analytics director
Pernod-Ricard is a leading worldwide Wine and Spirits company. This position was made possible thanks our very entrepreneurial, innovative and risk-taking culture from the beginning as the Group strongly extended its geographical and products footprint across time, starting from absinthe and anise drinks in France to a portfolio of 400+ brands brought to customers and consumers across 160+ countries.
While leveraging digital, date and AI is becoming increasingly critical for consumer goods companies, Pernod Ricard, in line with its entrepreneurial culture, has the ambition to conquer new frontiers and be the most innovative Wine & Spirits company in the world in terms of AI and digital. The ambition is to leverage the uniqueness of the depth of our brand portfolio to address the right product & service at the right time, at the right price to the right person (at a time when market fragmentation is increasing in the Wine and Spirits sector). This is be done by
- Reinventing the way sales forces operate, equipping them with data-driven insight supporting the prioritization of their efforts
- Optimizing the pricing of products in real time.
- Optimizing marketing spend allocation across channels
- Framing new opportunities in supply chain, finance, B2B
Job aim:
We’re looking for a passionate and talented Machine Learning Engineer Manager to join our rapidly growing team. In this role, you’ll have the chance to roll up your sleeves to develop your team and contribute technically to our success. Successful candidates are intellectually curious builders who are biased toward action, scrappy, and communicative.
Roles and responsibilities:
The main mission of Machine Learning Engineers is to ensure our models can scale from a technical standpoint in close collaboration with Data Scientists, Analysts & Research scientist. This mission is done by direct contribution (test & implement new tool/micro-services, refactoring part of the model…) or with close collaboration with the team (peer programming, provide external feedback…)
As leader of the team, you role will be to empower your team members with good practices, regular feedbacks, training suggestion and assistance when tech or human challenges appear.. You will contribute to the success of our KEY DIGITAL PROGRAMS by:
Being a great leader:
- Recruit & assign roles to each team member considering their skills & expectations
- Assist & coach your direct reports or other relevant contributors on both technical excellence as well as developing good soft skills
- Animate your team, build rituals while promoting collaboration with the rest of the organization
- Suggest & embark teams on embracing relevant new practices, tools or organization that will have a positive impact on products as well as team well-being
- Work closely with the data IT team to improve the technical tools and ecosystem to stabilize our products
- Guide non-technical teams in understanding analytics at scale, infrastructure as code and best practices for robust software development
Contributing to our technical excellence
- Identify opportunities across our program to create convergence, manage priorities & embark everyone in the journey
- Apply software development practices and standards to develop robust and maintainable software
- Maintain an active role in every part of the software development life cycle
- Optimize and enhance computational efficiency of algorithms and software design
- Partner with Data Engineer & Data Scientist to scale prototypes models to robust models
- Work closely with Data IT teams to ensure that we maintain good industrialization level considering maturity of products, market specificity & investment available
- Interact directly with KDP teams on new features for future product releases
- Share software design and solutions ideas
- Actively contribute to Data platform community
Job Scope :
- Key External stakeholders: Consulting firms, Tech companies
- Internal stakeholders: Data scientist, Data Analyst, Data Engineer, IT Platform lead, Project managers, experts
- Job scope: 100% international
Why joining us:
- Working at Pernod-Ricard is the perfect place for you to develop your technical skills in a holistic way:
- We setup transversal squad, allowing you to work in multidisciplinary teams deeply integrated with business and market. You will develop both technical skills and business / soft skills.
- Top-notch team & tools:
- Our team encompasses experienced and proven experts
- We already have a central data platform in Azure connected to markets through snowflake.
- Our platform team is already in place and uses cutting-edge tools to build & maintain applications, data science models & pipelines (Datalake, Databricks, Azure Data Factory, Dockers)
- Variety of projects and day-to-day work:
- We are present in 160+ markets with 400+ brands globally, we can propose an endless variety of projects.
- We develop unique solution for our unique internal clients
- Our commitment for a multi-year transformation journey will allow you to participate in projects with different maturities: from proof of concept to production.
- Your day-to-day work will be varied as our team will focus on 3 priorities: push forward boundaries (imagine creative solutions to hack Pernod-Ricard), delivering qualitative tech assets for the company and facilitate adoption of the solution across the company.
Conviviality at work:
How many of us have been in a job where we can truly be ourselves, where we get up every day feeling at ease and confidant to share who we are with people we work with? At Pernod-Ricard we are Proud to Belong, Empowered to Perform and Committed to Care.
We call it conviviality. We believe that this spirit should flow through to your work.
Your Profile:
Soft skills
- Ability to build & share a common vision
- Ability to detect & retain talents
- Good at organizing, processing & prioritize tasks
- Good communication skills
- Establish trust and genuine connections, motivate people accordingly.
- Pragmatic and capable of solving complex issues
- Ability to understand business needs
- Push innovative solutions
- Service-oriented, flexible & team player
- Self-motivated, take initiative
- Attention to detail & technical intuition
Hard skills
Experience in software development methods (illustrative)
- Exposure to analytics applications or experience building analytics tools
- Familiarity with data science methods and scaling data science methods
- Proficiency with infrastructure as code principles
- Familiarity with the storage, manipulation and management of relational, non-relational and streaming data structures
- Analytic reasoning and complex problem solving involving mathematical programming and big data problems
- Understanding of parallel computing
Familiarity with a broad base of analytics tools (illustrative)
- Good knowledge of cloud computing. Knowing Azure is a plus
- Languages programming: Python, GO, C++, Java, Scala, JavaScript, TypeScript
- DevOps: Docker, Kubernetes, CI/CD, Terraform, unix-based command line
- Full stack development: GraphQL, React
- Data: SQL, Spark, Hadoop
- Data Science and machine learning (Pandas, Scikit learn)
- Deep learning (Tensorflow, Keras etc.)
- Project management & support : JIRA projects & service desk, Trello, Confluence, Sharepoint
Past experience
- Masters Degree in Computer Research Science, Statistics, Operations Research, or related field
- 8+ years of experience in a software development environment
- Experience in an FMCG company is a strong plus
If you don’t fill 100% of the criteria below don’t panic, we expect you to learn with us in this position
Pernod Ricard values diversity and solidarity within its organization and in its relations with its stakeholders. Our recruitment methods focus on skills and we welcome all types of talent.
Job Posting End Date:
Target Hire Date:
2022-12-05-08:00 Target End Date:
