General background on position

• This position is part of Shell’s growing Finance & Data Operations Commercial Data Science Team.


• With 150+ data scientists based primarily in Chennai and Krakow, Commercial Data Science team is a key digitalization partner to Shell’s Upstream, Integrated Gas, Renewables and Downstream business units.


• This team delivers fit for purpose data science solutions from proof-of-concept to deployment for Shell’s global assets and provide tangible commercial value to business units within Shell by enabling data-driven decision making.


• The data scientist will join a high growth global data science team to support senior stakeholders with data driven commercial decision making in renewable energy business.

Key responsibilities of the role

• Responsible for ensuring right modeling approach(es) for given scenario and articulate why the approach fits, assess data availability, modeling feasibility, evaluate validity of the model (both scientifically as well as from the business perspective) and review interpretation of model results


• Must quickly mine data sources, analyze large datasets, support hypothesis generation, develop PoC and evaluate data solutions for their statistical robustness.


• Work with Shell stakeholders and subject matter experts - across geographies and organizational boundaries - to identify opportunities for leveraging data to solve business problems and work collaboratively in a team environment.


• Articulate the insights and recommendations from the analysis in a business-friendly language and explain the workings of the model for business adoption


• Support the Data Science Team Lead in design and execution of analytics projects within the renewables and energy solutions portfolio.

Requirements

Education & Experience

• Strong background in quantitative skills gained from Tier 1 institutes
  
  
  
  • Master’s degree in business/ statistics/ mathematics/ computer science/economics/ quantitative finance OR
  
  
  • Engineering with strong experience in solving business problems by statistical or mathematical approach.
  
  
  
  


• 4+ years of relevant experience

Industry / Functional expertise

Prior experience as an analytics/BI professional OR expertise in one of the following: techno-economic modelling, sales & marketing. Project experience in renewable energy, automobile, retail sectors preferred. Functional expertise in any one or more of the following industries / functional areas:

• Techno-economic modelling: Optimization of renewable energy asset configuration based on defined economic parameters, scenario, and sensitivity analysis


• 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


• Proficiency Level: Skill

Modeling and Technology Skills

• Solid foundation in machine learning techniques (supervised and unsupervised), statistics / mathematics / operations research including (but not limited to) Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modeling, Affinity & Association, Time Series, distribution / probability theory.


• Exposure to linear and non-linear programming, simulation-based optimization methods


• Strong experience in analytics tools and technologies (including, but not limited to)
  
  
  
  • Python, R
  
  
  • SQL
  
  
  • Alteryx, Power BI
  
  
  • MS tools including Excel and Power Point
  
  
  
  


• Proficiency in code management / version control tools such as GIT, DevOps


• Awareness of Agile / Scrum ways of working


• Story telling - present recommendations and insights from data in an easy and compelling way


• Passion for data with strong analytical mindset and focus on drilling data for commercial insight


• Learner mindset with demonstrated ability to identify skill/experience gaps, take proactive steps to close them and quickly deploy skills the from new learning to business problems.


• Proficiency Level: Skill

Stakeholder Management Skills

• Have an entrepreneurial approach towards helping growing pool of stakeholders understand value from data science approaches.


• Comfortable to quickly adapt to stakeholder requirements, demonstrate flexibility in identifying and deploying appropriate data science solution from a wide range of tools and techniques with a sharp focus on providing commercial insights


• Remain engaged with stakeholders and be resilient in the face of delays, setbacks, and uncertainty


• Fluent in communicating (verbal and written) with senior global stakeholders who could be from diverse engineering and business backgrounds


• Work collaboratively across diverse stakeholders’ groups in a team environment – business SMEs, IT, data teams, analytics resources, etc. to provide end to end project deliverables


• Ability to work under pressure with tight deadlines, across time-zones with virtual teams


• Deliver actionable insights and recommendations that directly address business challenges / opportunities


• Clearly articulate the assumptions, risks, and upsides of the analysis recommendations


• Understand business KPI's, frameworks and drivers for performance


• Proficiency Level: Skill