Data Scientist

**Data Scientist (Marketing Analytics)**

**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.
- The role involves close collaboration with the global marketing analytics lead to work with markets to build and maintain data science models to provide marketing insights to the business.

**Purpose**
- Develops analytics models using specialized tools based on the business problem and data available to provide valuable marketing analytics solutions to the business needs.
- Identifies the right set of 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 Lead & Digital Product Owners in design and execution of analytics projects
- Works closely with the marketing analytics lead and with marketing and sales stakeholders in the business to ensure that models meet business needs

**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
- Manage and drive the data collection part and setup guidelines on the data format.

**Industry / Functional Expertise**
- Industry Experience in Oil & Gas - Downstream business or other Mobility business would be desirable.
- **Functional expertise in**
- Hands-on experience in Marketing Mix Modelling 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)

**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:

- Python - Essential
- R & Power BI/other visualization experience - Desirable
- SQL - Ideal
- 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
- Up-skill data science team with specialized MMM knowledge.
- Dimensions
- Support design and delivery of analytics projects, within Downstream or cutting across other business units within Shell

**Experience**
- 4+ years of relevant experience (Practical 2+ years’ experience in marketing mix modelling)
- Advanced university degree in Mathematics, Statistics, Engineering, Economics, Quantitative Finance, OR, etc.
- Excellent written and verbal communication skills