AGM - Data Analytics
2 weeks ago
OVERALL PURPOSE OF THE JOB
Already 2nd largest market of the group Pernod Ricard and with strong tailwinds, Pernod Ricard India has a very ambitious agenda. To help refining its vision / ambition and ensure that the organization is delivering towards it, a dedicated Transformation team was created in July 2022. The Transformation team's mission is to build and scale up future focused capabilities especially around digital, data, and analytics, also in strategy, PMO, M&A-, and new businesses. Created 2+ years back and initially incubated within Commercial. The Data Analytics team is now part of Transformation as we want to bring into the next level, i.e., impacting projects across the organization (while ensuring strong Commercial support still). Also, that move is coincidental to the creation of a Data Governance team in May 2024. Its purpose is to enhance the data quality across the organization and hence is highly connected and synergetic with the data analytics team.
CONTEXT
Data maturity: while PRI is creating and consuming a lot of data, its usage is sometimes - Decentralized leading to team by team interpretations. - Manual underleveraging the impact we could have using such data
Digital projects: PRI drastically increased its use of data, across key digital programs. Affiliate saw an acceleration of data-led initiatives in the past 2 years (including Dstar, Matrix, Maestria, other AI) Data governance: that team will benefit from and closely collaborate with the new data governance team we are setting up this coming May PR India JD \ AVP – Digital Transformation
HQ Analytics: PR HQ Digital teams act as the key functional relay for such initiatives and programs with the expertise in Data Science & Data Governance providing guidance and resources to PRI
KEY RESPONSIBILITIES
1. Lead a team operationally to deliver high-quality insights that support business decisions by
Leveraging the past work delivered in the past 2+ years and the solutions established to create the transversal data analytics roadmap for PRI.
Drive implementation/ outcomes on across businesses and functions including (but not limited to) Commercial, ,Supply chain, Consumer Insights, etc.
Remaining results oriented thanks to a clear focus on value, effort & feasibility from discovery to continuous improvement of our digital products
Support the growing AI agenda led by the group / HQ, for which PRI is a pioneer and has already delivered significant projects
Engaging Sales programs directors and leaders to ensure good integration and effective ways of working with all teams / departments
Reporting team progress to Chief Transformation Officer, key business sponsors, & general management
2. Create & maintain a convivial working environment by
Helping colleagues maintain a good work / life balance ratio, in particular help everyone in need when facing challenging such as tight deadline, technical or human problem
Coaching team members on their tech & soft skills in adequation with their current mission
Proactively help to identify and overcome conflicts which are part of any collaboration.
Working closely with Data Engineer, Data Scientist, Data Manager, Designers, Machine Learning Engineer & Product Owner to create synergies between teams
3. Collaborate with cross-functional teams to identify business requirements and translate them into action plan
Arbitrating on business initiatives prioritization to ensure alignment with Product Owners
Getting sponsorship of business directors to setup adequate projects and resources
Identifying proactively all program's needs, evaluate the opportunity to launch, postpone or stop part of our program
Explain proactively with other department / functions what the purpose of the teams and best way to interact with
Oversee data projects from inception to completion, ensuring they are on track, within budget, and meeting quality standards.
KEY INTERFACE
INTERNAL
Zonal Commercial & Marketing Teams
Strategy and Transformation teams
IT Team - Any business team
Global Analytics Team
MIS & Analytics Teams
EXTERNAL
Consultants depending on projects
JOB REQUIREMENT:
QUALIFICATIONS
➢ MBA degree from a top tier business school
➢ Engineer undergrad or data related qualification a plus EXPERIENCE
➢ 10-15 years in analytics functions, with at least 5 years of significant advanced analytics leadership in Consumer led industries
➢ -Experience in working high potential profiles on international programs
➢ Strong data champion with growth mindset and enthusiastic about delivering projects with business impact
➢ Provide leadership, best practices, and standards required to deliver effective Data Governance initiatives across an organization
➢ Curious & quick learner able to deep dive in each Pernod Ricard business area and identify priorities
➢ Strong communication and interpersonal skills, able to liaise with staff at all levels, get sponsorship from key business leaders and produce communication content with impact PR India
➢ Good listening skills and able to explain complex concept to non-technical audience
➢ Can-do attitude, able to work under high velocity and manage large diversity of projects
➢ Strong analytical skills and problem-solving mind-set with ability to see the big picture
If you don't fill 100% of the criteria below don't panic, we expect you to learn with us in this position
SKILLS AND KNOWLEDGE
➢ Pragmatic and capable of solving complex issues, result-oriented and capable of challenging other stakeholders, ability to understand business needs, good communication, push innovative solutions, self-starter who thrives in a collaborative environment, ability to help all stakeholders understand & arbitrate pragmatic decisions that will drive data science roadmap
➢ Tools / Language: Python, usage of Git, familiar with one Cloud provider (Azure is a +), Storage (Azure Datalake, Snowflake) processing and orchestration (Databricks, ADF, LogicApp), exploration (Power BI), API Management and Azure Functions for serverless applications, Statistics (t-tests, ANOVA), segmentation/clustering techniques, predictive modeling: e.g. logistic regression, linear regression, machine learning: e.g. LCA, Random Forest, neural networks, time series forecasting: (seasonality decomposition, ARIMA), Optimization: e.g. linear programming, heuristic, knowledge on ML Engineering / Software Engineering
➢ Ability to connect and influence the business, understand the business problematics, and bridge data analytics with real life
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