Data Science Team Lead

Role:

• This position is part of Finance & Data Operations Data Science team leading a small team of data scientists delivering advanced analytics projects for different businesses within Shell. The individual will join a growing global data science organization spanning both on/offshore.
• Incumbent is responsible for developing analytical models for projects collaborating with different business stakeholders & other partners and working across a range of technologies and tools.
• Critical skill: Managing tough stakeholders and exceeding their expectations. This role has very demanding global stakeholders and the candidate will need to work closely with them and ensure error free delivery of existing projects. Also will need to demonstrate ability and skills required for taking on advanced analytics projects
• The ideal candidate has strong background in quantitative skills (like statistics, mathematics, advanced computing, machine learning) and has applied those skills in solving real world problems across different businesses / functions.
• Candidates will need to develop deep expertise in Shell data sources and operation of analytical tools so that they can not only answer business questions but follow their own initiative to further drill down to find the true underlying reasons. Business Questions are likely to relate to Range optimisation, Promotion effectiveness, On-Shelf availability, Pricing optimisation, Performance decomposition, Store clustering and identifying purchase patterns.

Dimensions :

• Lead the execution of analytics projects within the portfolio
• Design and articulate the data science solution relevant to the business problem / opportunity
• Lead identification of appropriate data science models and evaluate their fitment for the available data
• Articulate the insights from the models in business-friendly language and explain the workings of the model for business adoption
• Provide support to the business value manager in managing the portfolio

Education Requirement/Field of Study:

Project Management

• Execute end-to-end analytics projects - Project scoping, sourcing data, managing modeling, translating model results into business insights, and helping business partner understand insights and make decisions accordingly (help generate value for organization through analytics)
• Creating project management plan, running status update meetings, coordinating deliverables and timelines, and managing risks to project delivery
• Recognize the level of statistical knowledge in business stakeholders vs. analytics experts vs. IT resources and articulating how analytics will be applied appropriately
• Manage different moving parts - business stakeholders, IT, Analytics Resources, Data Experts, SMEs, etc. for the successful execution of the projects (executing multiple projects at a time will be considered a plus)
• Proficiency Level: Mastery

Special Challenges

• Deliver practical working solutions from a new and developing conceptual area.
• Develop understanding of data analytics in colleagues to the level they each require recognizing that level is very different for different stakeholders and project team members.
• Virtual working with network of colleagues located throughout the globe.

Requirements :

Stakeholder Management Skills

• Working with demanding and difficult stakeholders who are highly analytical. The candidate should be able to demonstrate advanced analytics skills to them and ensure all projects are error free
• Forming close relationships with business stakeholders across businesses / functions to comprehensively understand their areas of operation and apply those in project execution
• Clearly articulate the challenges / opportunities in business / function that can be supported by analytics
• Deliver actionable insights that directly address challenges / opportunities
• Guide articulation of business insights and recommendations (based on model output) based on understanding of business / function and respective stakeholders
• Understanding of business governance and control structures & selecting the right analytical approaches which are consistent with businesses control/governance framework
• Understanding business KPI's, frameworks and drivers for performance
• Proficiency Level: Mastery

Industry / Functional Expertise

• Pricing Analytics -Price Elasticity, Optimization, Price Trial Evaluation and Forecasting
• Customer / Marketing– churn prediction, cross-sell / up-sell, Market Basket Analysis, Product Recommendation, Marketing Mix Modeling, Campaign design and effectiveness testing, Network Modeling, Customer segmentation, propensity analysis, customer lifetime value, profitability analysis, Customer experience (incl. voice of customer), CRM, Loyalty program management,
• Supply Chain / Spend: Demand & Supply Forecasting, Spend Analytics, Vendor Scoring, Pricing analysis (buy-side), product substitution analysis, product portfolio optimization, Tail spend analysis, logistics / network / route optimization, Contract Compliance
• Proficiency Level:Skill-to-Mastery

Modeling and Technology Skills

• Deep expertise in machine learning techniques (supervised and unsupervised) statistics / mathematics / operations research including (but not limited to):
  • Statistics / Mathematics: Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modeling, Affinity & Association, Time Series, DoE, distribution / probability theory
• Strong experience in specialized analytics tools and technologies (including, but not limited to)
  • Python, R
  • Alteryx,Spotfire, Tableau
  • Ability to search, extract, load & visualize data from data bases using pre-defined reports and new ad hoc queries (using BI self service)
  • Proven ability to use visualization software packages – Spotfire, Tableau as an advantage and to make state of art presentations using MS ppt
  • Identify the right modeling approach(es) for given scenario and articulate why the approach fits
  • Assess data availability and modeling feasibility
  • Review interpretation of models results
  • Retail experience (Must) Convenience Retail experience ( good to have)
  • Master of MS Power Point (Must)
  • Story telling: capacity of presenting data in an easy and compelling way
  • Ability to work under pressure as numbers of request from business are growing and expectations is to grow even more due to the success of the work done so far
  • Strong analytical mindset and real passion for Data, drilling data for insight and learning new things every day in a pro-active way.
  • Evaluate model fit and based on business / function scenario
  • Proficiency Level:Mastery

Interested?