Data Scientist Job in Shell
Job Summary
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 models 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.
Purpose
Develops analytics models using specialized tools based on the Digital business problem and data available
Focus on capturing customers online behaviour across the Retail digital channels to help harness data as a strategic asset and drive business value.
Working directly with the IT and business leads, project managers and vendors to understand requirements and assist with digital analytics tagging deployment. This may include working with different projects to align requirements across programs and span multiple stakeholder groups.
Identifies the right set of data & models and develops the right code / package to execute them
Evaluates the validity of the model (both scientifically as well as from a business perspective)
Support the Data Science Team Lead 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, IT, Data teams, Analytics, vendors, resources, etc. to deliver on project deliverables and tasks
Identify actionable insights that directly address challenges / opportunities
Articulate business insights and recommendations to respective stakeholders
Understanding business KPI's, frameworks and drivers for performance
Consultation on measurement plans and analytics best practices.
Communication skills for managing stakeholder expectation on deliverables.
Proficiency Level: Skill
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.)
or
functional expertise in any one or more of the following industry / functional areas
Customer / Marketing customer experience 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,
Digital Product Experienced in Adobe analytics and customer online behavior tracking including:
Adobe analytics advanced user (Workspace, datawarehouse, tagging knowledge)
Tagging debuggers and strong understanding of how this impacts AA and how to fix and communicate with implementation team - MUST
Configuration of Adobe Analytics Report suites & technical debugging - MUST
QA data capture and mapping into the Report suites - MUST
Ability to extract actionable insights MUST
Support technical definition of measurement frameworks and reporting the different Customer Value Propositions contained within the Digital Channels - MUST
Manage effective customer online segmentation and profiling for use within the optimization services Nice to have
Support configuration of Data Feeds/Exports and general ETL of data passing between AEC and Shell solutions in line with applicable compliance procedures. - MUST
Help maintain the business focus on data quality in support of understanding the user experience. - MUST
Provide training and support to business stakeholders for online behaviour data i.e. training them to be self-serve for basic reporting or helping setup custom reports as needed - MUST
Lead on more advanced aspects of data ETL and visualisation (Domo) as needed - MUST
Identifying key online behaviour data elements associated with User Stories - MUST
Collaborate within a global team of Product Owners, Business Analysts and Project Managers to align product requirements - MUST
Working with business leads to develop/verify the business case for product enhancements; this will include research of online behaviour (past/present/future) and defining and tracking online success metrics
Supporting Business & Change Impact Assessments where required
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
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
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 models 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.
Purpose
Develops analytics models using specialized tools based on the Digital business problem and data available
Focus on capturing customers online behaviour across the Retail digital channels to help harness data as a strategic asset and drive business value.
Working directly with the IT and business leads, project managers and vendors to understand requirements and assist with digital analytics tagging deployment. This may include working with different projects to align requirements across programs and span multiple stakeholder groups.
Identifies the right set of data & models and develops the right code / package to execute them
Evaluates the validity of the model (both scientifically as well as from a business perspective)
Support the Data Science Team Lead 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, IT, Data teams, Analytics, vendors, resources, etc. to deliver on project deliverables and tasks
Identify actionable insights that directly address challenges / opportunities
Articulate business insights and recommendations to respective stakeholders
Understanding business KPI's, frameworks and drivers for performance
Consultation on measurement plans and analytics best practices.
Communication skills for managing stakeholder expectation on deliverables.
Proficiency Level: Skill
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.)
or
functional expertise in any one or more of the following industry / functional areas
Customer / Marketing customer experience 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,
Digital Product Experienced in Adobe analytics and customer online behavior tracking including:
Adobe analytics advanced user (Workspace, datawarehouse, tagging knowledge)
Tagging debuggers and strong understanding of how this impacts AA and how to fix and communicate with implementation team - MUST
Configuration of Adobe Analytics Report suites & technical debugging - MUST
QA data capture and mapping into the Report suites - MUST
Ability to extract actionable insights MUST
Support technical definition of measurement frameworks and reporting the different Customer Value Propositions contained within the Digital Channels - MUST
Manage effective customer online segmentation and profiling for use within the optimization services Nice to have
Support configuration of Data Feeds/Exports and general ETL of data passing between AEC and Shell solutions in line with applicable compliance procedures. - MUST
Help maintain the business focus on data quality in support of understanding the user experience. - MUST
Provide training and support to business stakeholders for online behaviour data i.e. training them to be self-serve for basic reporting or helping setup custom reports as needed - MUST
Lead on more advanced aspects of data ETL and visualisation (Domo) as needed - MUST
Identifying key online behaviour data elements associated with User Stories - MUST
Collaborate within a global team of Product Owners, Business Analysts and Project Managers to align product requirements - MUST
Working with business leads to develop/verify the business case for product enhancements; this will include research of online behaviour (past/present/future) and defining and tracking online success metrics
Supporting Business & Change Impact Assessments where required
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
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
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