Data Scientist

General Position Definition

• Finance & Data Operations Data Science Team is tasked with delivering tangible value to business units within Shell through data-driven decision making.
• This position is part of Finance & Data Operations Data Science team 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 solutions for projects collaborating with different business stakeholders & other partners and working across a range of technologies and tools.
• 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
• The role involves close collaboration with the Global Lubricant stakeholders to work with markets in building solutions for their data driven decision making

Purpose

• Develops dashboards/models using advance Machine Learning and specialized tools based on the business problem
• Quick understand of the data is a must to arrive at the decision based on the transactional data
• Support the Data Science Lead & Digital Product Owners in design and execution of analytics projects
• Work with Shell stakeholders and subject matter experts to complete tasks and deliverables on projects

Skills

Stakeholder Engagement Skills

• Working collaboratively across multiple sets of stakeholders –business SMEs, Digital Product Owners, IT, Data teams, Analytics professionals, data engineers etc. to deliver on project deliverables and tasks,
• Identify actionable insights that directly address challenges / opportunities
• Understanding business KPI's, frameworks and drivers for performance
• Articulate business insights and recommendations (based on model output) to Senior business stakeholders through presentations
• Proficiency Level: Skill

Industry / Functional Expertise

• Industry Experience in Oil & Gas - Downstream business or other B2B business would be desirable.
• Functional expertise in
  • Hands-on experience in Advance ML, Dashboarding at least 2 years required
  • Strong experience in other areas of Marketing Analytics domain would be essential:

Customer / Marketing – any of: Channel Attribution Studies, Campaign, pricing analytics, churn prediction, cross-sell / up-sell, Market Basket Analysis, Product Recommendation, 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, KPI frameworks for measuring campaigns, digital analytics (or similar use cases)

• Proficiency Level: Skill

Modeling and Technology Skills

• Deep expertise in machine learning techniques (supervised and unsupervised) statistics / mathematics / operations research including:
  • Statistics / Mathematics: Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modeling, Logit/Probit Model, Affinity & Association, Time Series, DoE, distribution / probability theory
  • Advanced Machine learning techniques: Decision Trees, Neural Networks, Deep Learning, Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction / engineering
• Strong experience in specialized analytics tools and technologies:
  • Alteryx & SQL - Essential
  • Power BI - Essential
  • R - Essential
  • Python & Power BI/other visualization experience - Desirable
• 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 and present them
• Evaluate model fit and based on business / function scenario
• Proficiency Level: Skill-to-Mastery

Special Challenges

• Rapid onboarding on projects, understanding analytics goal and working with ill-defined datasets
• Communicating technical jargon in plain English to colleagues within Data Science team and outside
• Virtual working with network of colleagues located throughout the globe
• Appreciation of how to apply marketing analytics to a (largely) B2B business context

Dimensions

• Support design and delivery of analytics projects, within Downstream or cutting across other business units within Shell

Experience

• 4+ years of relevant experience
• Advanced university degree in Mathematics, Statistics, Engineering, Economics, Quantitative Finance, OR, etc.
• Excellent written and verbal communication skills
• Good interpersonal communication skills and influencing skills & Client result oriented
• Quick to learn technologies and ability to work independently

Disclaimer