Data Scientist
- Shell
- 5 - 8 years
- Chennai
- 3 days ago
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Job Description
Job Description:
What s the role
- Controller and Finance Operations- Commercial Data Science Team is tasked with delivering tangible value to business units globally across Shell through data-driven decision making.
- This position is based in Shell Centre Chennai office with the primary responsibility to work on data science projects in Shell Energy TS PDS projects.
- Incumbent will be responsible for executing analytics projects using range of cloud technologies collaborating with different stakeholders in Finance Risk Business and IT as well as supporting the implementation of insights to realize tangible commercial value for Shell.
- The ideal candidate has strong background in quantitative skills (like statistics mathematics advanced computing machine learning) domain expertise in relevant business areas will be an advantage.
What you ll be doing
- Collaborate effectively with stakeholders and experts from various geographies and disciplines.
- Analyze diverse data sets related to Shell Energy Finance Risk and contribute to generate commercial value to Shell
- Assess identify data gaps establish and enforce data quality and documentation standards as well as controls across reporting and audit analytics solutions.
- Work with engineering and research teams on designing building and deploying data analysis systems for large data sets and extracting meaningful insights for Business.
- Articulate insights and recommendations from data analysis in a business-friendly language using impactful visualization techniques.
- Assist team lead and portfolio manager to identify project problems challenges or risks that could lower the value generation.
What you bring
- At least 5-8 years of working experience
- Significant experience in analytics or research role
- Degree in Management Mathematics Statistics Engineering Economics Quantitative Finance etc. Post Graduation is a plus.
- Experienced in Machine learning techniques: Linear regression Logistic Regression Decision Trees Random Forest Gradient boosting Neural Networks Deep Learning Support Vector Machines Clustering Hierarchical Models Bayesian Modelling Feature Reduction / engineering Anomaly detection.
- Statistics / Mathematics: Hypothesis testing Univariate / Multivariate Analysis Cluster Analysis Classification/PCA Factor Analysis Time Series DoE distribution / probability theory Causal Inference.
- GenAI application: Build effective RAG systems Agents Multi-Agent Systems. Skilled in prompt engineering techniques.
- Computer Science: Functional Programming Object Oriented Programming System Design SOLID Principles Design Patterns Version Control (Git)
- Strong experience in the following
- Strong experience in SQL Python
- Visualization PowerBI Qliksense
- Databricks Github experience
- Exposure to data quality Data validation techniques.
- Strong experience in proactively identifying data defects inconsistencies and breaks; partner with Technology teams to drive prioritization and resolution Skilled in Exploratory data analysis.
- PL Analysis: Conduct comprehensive reviews of profit and loss drivers summarizing key drivers and generate automated commentary.
- Forecasting: Forecast PL and working capital using predictive analytics.
- Variance Analysis: Identify and explain deviations between actual results and forecasted figures highlighting key contributing factors.
- Scenario Planning Stress Testing: Evaluate exposures PL fluctuations and liquidity positions under various stressed market conditions to assess resilience.
- Financial Process(AR/AP): Skilled in identifying process gaps implementing improvements ensuring data integrity and supporting automation or analytics initiatives to enhance operational efficiency and financial transparency.
- Work with Lead and Manager to accurately assess different business use cases and then break them down into smaller problems
- Estimate effort involved in projects and be comfortable to work in an agile environment.
- Follow uphold Computer Science Engineering(Data Science) guidelines Technical Audit guidance for all projects
- Have an entrepreneurial approach towards helping a growing pool of stakeholders understand value from data science approaches for Shell Energy TS Process Data Systems.
- Fluent in communicating (verbal and written) with other data science team members and global stakeholders who could be from diverse engineering business Finance backgrounds.
- Ability to articulate the assumptions risks and upsides of the analysis recommendations.
- Understand business KPIs frameworks and drivers for performance.
- Remain engaged with stakeholders and be resilient in the face of delays setbacks and ambiguity.
- Proactively voices insights and concerns and takes responsibility for resolving assigned problems
- Ability to anticipate challenges risks and proactively seeking guidance from senior portfolio managers when necessary.
- Effectively communicates the strengths and limitations of proposed solutions in stakeholder friendly terms to support informed decision making.
- Learner Mindset look for challenges speak up learn from failures and setback.
Job Classification
Industry: Oil & GasFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Full Stack Data ScientistEmployement Type: Full timeContact Details:
Company: ShellLocation(s): Chennai+ View Contact
Keyskills: Computer science Automation Data analysis Renewable energy LNG System design Analytics SQL Auditing Python
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