Data Scientist

Job aim:

We’re looking for a passionate and talented Data Scientist to join our rapidly growing team. In this role, you’ll have the chance to roll up your sleeves and apply data science methods and analytics to sustain Pernod-Ricard growth. Successful candidates are intellectually curious builders who are biased toward action, scrappy, and communicative.

Context:

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.

Leveraging digital, data and AI is becoming increasingly critical for consumer goods companies—it is becoming self-evident that the champions of those topics will be the leaders of today and tomorrow:

• AI and Data are shaping new ways to do business in the Consumer sectors with high-value applications such as end-to-end forecasting and planning along with ROI measurement for advertising and promotional spending.

• This trend is reinforced by fast-moving and complex industry challenges, which further increases the need to anticipate, adapt to, and shape changes in consumer demand and behavior.

In this context, 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 will be done by

• Reinventing the way sales forces operate, equipping them with data-driven tools supporting the prioritization of their efforts

• Optimizing the pricing of products in real time.

• Optimizing marketing spend allocation across channels

We have already started this transformation agenda

• We have already deployed some flagship projects, e.g.,

  • Prioritization in France and in the US of Sales Forces allocation across points of sales based on business potential and image by using various sources of data (point of sales, sales data by SKU, Sales Rep data, social network, third-party data)

  • Prioritization of outlets through social media data & automated updates to increase market penetration and better calibration of our route to market

• We have launched a global transformation program on Data & AI with strong sponsorship from the CEO and his top management and large financial investment.

• Projects are delivered in production on our “Data Platform” built in partnership with our best in class IT team leveraging the most recent technologies available on the public cloud.

• We built in partnership with our HR team a Data Academy program to certify internally our employee from “Grape to XO level

Roles and responsibilities:

To help deliver the expected value on our Key Digital Programs, you will integrate the Data, Design and Analytics team where various profiles work together (Data Scientists, Data Analysts, Machine Learning Engineer, Design team, Data Office team). The purpose of the position is to support the life cycle of our digital solutions we aim to deliver to our affiliates for them to boost their digital acceleration.

Build relevant data science products for our markets

• Understand business issues and translate these into technical needs 

• Gather and organize large and complex data assets, perform relevant analyses and modeling

• Ensure Analytics model quality assurance and validate them (peer validation)

• Define model monitoring criteria

• Communicate hypotheses and findings in a structured way

Collaborate to industrialize, maintain, and improve our data science products

• Partner with Data Analyst team to present outcomes of our models

• Partner with Data Steward to identify necessary data to build our models

• Partner with Data Engineer to build necessary data pipelines

• Work closely with Data industrialization team (IT) to ensure that the POC will be eligible for industrialization

• Leverage existing or create new data science capabilities within Pernod-Ricard to bring value through business use cases

• Actively contribute to Data Science community

Job Scope :

• Key External stakeholders: Consulting firms, Tech companies

• Internal stakeholders: IT data scientist, IT Platform lead, Project managers, experts

• Job scope: 100% international

Profile required:

Soft skills

• Pragmatic and capable of solving complex issues

• Result-oriented and capable of challenging other stakeholders

• Good listening

• Ability to understand business needs

• Good communication

• Push innovative solutions

• Self-starter who thrives in a collaborative environment

Hard skills

Good knowledge of Python and GiT

Experience in core analytics methods (illustrative)

• Statistics (t-tests, ANOVA)

• Segmentation/clustering techniques

• Geographic cluster recognition and manipulation techniques

• Predictive modeling: e.g. logistic regression, linear regression

• Machine learning: e.g. LCA, Random Forest, neural networks

• Network analysis (location-allocation, traveling salesperson, vehicle routing problem)

• Time series analysis (ARIMA, VAR, etc.)

• Text mining & unstructured data analytics

• Simulation: e.g. MC, dynamic, discrete event

• Optimization: e.g. linear programming, heuristic

Familiarity with a broad base of analytics tools (illustrative)

• Good knowledge of cloud computing. Knowing Azure is a plus

• Data tools: Storage (Azure Datalake, SQL Database, AAS), processing and orchestration (Databricks, ADF, LogicApp), exploration (Power BI, Superset), API Management and Azure Functions for serverless applications

• Project management & support: JIRA projects & service desk, Trello, Confluence, Sharepoint

Past experience

• Data science experience in a large company

• 2-5 years as a Data Scientist with extensive experience in building analytical solutions

• Experience in an FMCG company is a strong plus

Joining us

Working at Pernod-Ricard is the perfect place for you to develop your Data Science skills in a holistic way:

• We use Agile ways of working, 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 core data science team is already in place and uses cutting-edge data science tools to answer business questions (machine learning, deep learning, statistical learning, optimization)

  • Our primary language is python but we are open to test and incorporate any language that fits our needs (be ready to learn!)

• 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.

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.

Job Posting End Date:

Target Hire Date:

2023-01-02-08:00

Target End Date: