Data Scientist Specialist

Key Skills

Python Programming, C++, PowerBI, QlikView, Tableau, R Programming, Spotfire

Job Description

Accountabilities:

• 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 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 leading and executing analytics projects in a business, collaborating with different business stakeholders and other partners, support the implementation of insights to realize tangible value for Shell 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), brings domain expertise, has applied those skills in solving real world problems across different businesses / functions.
• Support the Data Analytics team in design and execution of analytics projects
• Work with data and technology experts to help execute analytics projects and deploy solutions
• Support design and delivery of analytics projects, within or cutting across upstream and downstream business units in Shell
• 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

Skills & Requirements:

• Industry / Functional Expertise in either:
  • Manufacturing / Energy
  • Customer / Marketing 
  • Supply Chain / Spend
  • Functional Analytics
  • Trading & risk management
  • Forecasting
• 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, NLP, NLG, AND/OR;
• 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, AND/OR;
• Operations Research: Sensitivity Analysis – Shadow price, Allowable decrease or increase, Transportation problem & variants, Allocation Problem & variants, Selection problem, Multi-criteria decision-making, models, DEA, Employee Scheduling, Knapsack problem, Supply Chain Problem & variants, Location Selection, Network designing – VRP, TSP, Heuristics Modeling, AND/OR;
• Risk: Simulation design and high-performance computing, GARCH modeling, Macro-economic / Market behaviour modeling AND/OR;
  • SAP/ Finance Knowledge will be an asset
  • Strong experience in specialized analytics tools and technologies (including, but not limited to)
  • Python, R, C++ 
  • Power BI, Spotfire, Tableau, Qlickview
• 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 – SAP Business Objects (must) and Power BI, Spotfire, Tableau as an advantage and to make state of art presentations using MS ppt
• Advanced skills in design of easy-to-use reporting and interactive dashboards in SAP Business Object
• 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 based on business/function scenario
• 2+ years in a global role or in various locations
• Bachelors / Masters degrees in Mathematics, Statistics, Engineering, Technical Finance, Econometrics, or other quantitative areas