Shell Hiring Data Scientist

Location: Chennai
Experience: 3+ Years
Skill: Knowledge for Data Scientist

Requirements
Industry / Functional Expertise

  • Provide deep business expertise preferably Oil & Gas – Upstream or Downstream businesses. (If these are not available, willing to consider other industries that are similar or related – manufacturing, mining, power generation, etc.)
  • functional expertise in any one or more of the following industry / functional areas
  • Manufacturing / Industrial: Equipment Failure prediction, Maintenance Scheduling & Optimization, Inventory optimization, Cost Diagnostics, Energy Management
  • Customer / Marketing – pricing analytics, 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
  • Functional Analytics: Order-to-cash, Procure-to-Pay, Record-to-Report, Tax (Direct & Indirect), Financial Risk and Assurance (controls and governance), Master Data Management, Inter-group / Intra-group
  • Trading & Risk Management: Across Credit & Market Risk – Value at Risk (VAR), Back testing, Stress testing
  • Proficiency Level: Skill
    Modeling and Technology Skills
  • Deep expertise in machine learning techniques (supervised and unsupervised) statistics / mathematics / operations research including (but not limited to):
    • Advanced Machine learning techniques: Decision Trees, Neural Networks, Deep Learning, Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction / engineering, Anomaly deduction, Natural Language Processing (incl. Theme deduction, sentiment analysis, Topic Modeling), Natural Language Generation
    • 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
  • Typically, each role will look at one of two of the above skills – not all of them
  • Strong experience in specialized analytics tools and technologies (including, but not limited to)
    • SAS, Python, R, SPSS (preferably two out of 4)
    • Spotfire, Tableau, Qlickview
    • For Operations Research (AIMS, Cplex, Matlab)
    • Awareness of Data Bricks, Apache Spark, Hadoop
    • Awareness of Agile / Scrum ways of working
  • 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
  • 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
  • Dimensions
  • Support design and delivery of analytics projects, within or cutting across upstream and downstream business units in Shell
  • Experience
  • 3+ years of relevant experience
  • Advanced university degree in Mathematics, Statistics, Engineering, Economics, Quantitative Finance, OR, etc.
  • Good interpersonal communication skills and influencing skills
  • Eagerness to learn and ability to work with limited supervision