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Shell Business Operations

Data Scientist - Senior Specialist

Shell Business OperationsO firmie

Shell Business Operations

Czerwone Maki 85

Kraków

Royal Dutch Shell is a global group of energy and petrochemicals companies, operating in over 80 countries and territories and employing more than 90,000 people. Our core values of Honesty, Integrity and Respect for People define who we are and how we work. Royal Dutch Shell has developed a global network of Shell Business Operations to provide first-class services to Shell companies across the world.

Shell Business Operations (SBO) Krakow sits at the centre of Shell’s global businesses, providing an operational backbone to our essential business functions. Working in a vibrant community with strong values and a supportive culture, an SBO-Krakow job will offer the chance to build a lasting and meaningful career. As one of seven Business Operations centres, located worldwide, a job in Krakow will give you the chance to interact and work with people across the world, helping to deliver excellent support to business clients and internal stakeholders as well as advanced financial operations.

Shell is an Equal Employment Opportunity Employer of Minorities, Females, LGBT Equality and Individuals with Disabilities.

Thanks to cooperation with Shell you gain: 

  • Comfortable working environment: Newly-built modern office with its own canteen, relax rooms, bike & car parking space
  • Yearly bonuses and lots of non-monetary benefits (e.g. MultiSport Card, vouchers for cultural and free time activities, 12 sport sections, and many more)
  • Complex medical care and individual life insurance
  • Additional funds for trainings and certifications
  • EuroShell Card
  • Bonus for referring your friend to work

People with disabilities are welcome to apply as we provide reasonable accommodations and assistive technologies for people with diverse disabilities.

Data Scientist - Senior Specialist
Miejsce pracy: Kraków
103199BR
Job Description

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 business problem and data available
  • 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 Team Lead in design and execution of analytics projects
  • Work with Shell stakeholders and subject matter experts to complete tasks and deliverables on projects
Requirements

Stakeholder Engagement Skills:
  • Working collaboratively across multiple sets of stakeholders – business SMEs, IT, Data teams, Analytics 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
Industry / Functional Expertise:
  • 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
  • Supply Chain / Spend: Demand & Supply Forecasting, Spend Analytics, Vendor Scoring, Pricing analysis (buy-side), product substitution analysis, product portfolio optimization
  • Functional Analytics: Order-to-cash, Procure-to-Pay, Record-to-Report, Tax (Direct & Indirect), Financial Risk and Assurance (controls and governance), Master Data Management
  • Trading & Risk Management: Across Credit & Market Risk - (VAR), Back testing, Stress testing 
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
  • 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
  • Risk: Simulation design and high-performance computing, GARCH modeling, Macro-economic / Market behaviour modeling
  • Process Analytics Process Discovery / Mining, BottleNeck analysis, Confirmation Testing, Process Benchmarking, Gap-to-Potential Assessment, SAP Data Models, SAP Table Structures; General Ledger Accounting, Accounts Payable, Accounts Receivable, Purchasing, Inventory Management, Material Planning, Invoice Verification, Material Requirement Planning (MRP), Warehouse Management, Vendor Valuation, Sales, Sales, Shipping and transportation, Billing or Invoice generation
  • Strong experience in specialized analytics tools and technologies (including, but not limited to)
  • SAS, Python, R, SPSS, Spotfire, Tableau, Qlickview
  • For Operations Research (AIMS, Cplex, Matlab)
  • Awareness of Data Bricks, Apache Spark, Hadoop
Experience:
  • 7+ years of relevant experience
  • Good interpersonal communication skills and influencing skills
  • Eagerness to learn and ability to work with limited supervision
 
Find out more
 
People with disabilities are welcome
 

Thanks to cooperation with Shell you gain: 

  • Comfortable working environment: Newly-built modern office with its own canteen, relax rooms, bike & car parking space
  • Yearly bonuses and lots of non-monetary benefits (e.g. MultiSport Card, vouchers for cultural and free time activities, 12 sport sections, and many more)
  • Complex medical care and individual life insurance
  • Additional funds for trainings and certifications
  • EuroShell Card
  • Bonus for referring your friend to work

People with disabilities are welcome to apply as we provide reasonable accommodations and assistive technologies for people with diverse disabilities.

Data Scientist - Senior SpecialistNumer ref.: 103199BR
Job Description

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 business problem and data available
  • 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 Team Lead in design and execution of analytics projects
  • Work with Shell stakeholders and subject matter experts to complete tasks and deliverables on projects
Requirements

Stakeholder Engagement Skills:
  • Working collaboratively across multiple sets of stakeholders – business SMEs, IT, Data teams, Analytics 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
Industry / Functional Expertise:
  • 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
  • Supply Chain / Spend: Demand & Supply Forecasting, Spend Analytics, Vendor Scoring, Pricing analysis (buy-side), product substitution analysis, product portfolio optimization
  • Functional Analytics: Order-to-cash, Procure-to-Pay, Record-to-Report, Tax (Direct & Indirect), Financial Risk and Assurance (controls and governance), Master Data Management
  • Trading & Risk Management: Across Credit & Market Risk - (VAR), Back testing, Stress testing 
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
  • 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
  • Risk: Simulation design and high-performance computing, GARCH modeling, Macro-economic / Market behaviour modeling
  • Process Analytics Process Discovery / Mining, BottleNeck analysis, Confirmation Testing, Process Benchmarking, Gap-to-Potential Assessment, SAP Data Models, SAP Table Structures; General Ledger Accounting, Accounts Payable, Accounts Receivable, Purchasing, Inventory Management, Material Planning, Invoice Verification, Material Requirement Planning (MRP), Warehouse Management, Vendor Valuation, Sales, Sales, Shipping and transportation, Billing or Invoice generation
  • Strong experience in specialized analytics tools and technologies (including, but not limited to)
  • SAS, Python, R, SPSS, Spotfire, Tableau, Qlickview
  • For Operations Research (AIMS, Cplex, Matlab)
  • Awareness of Data Bricks, Apache Spark, Hadoop
Experience:
  • 7+ years of relevant experience
  • Good interpersonal communication skills and influencing skills
  • Eagerness to learn and ability to work with limited supervision

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