Position:
• Data Science Analyst
Company:
• Shell
Location:
• Chennai, India
• Bangalore, India
Job type:
• Full time
Job mode:
• Hybrid work arrangement
Job requisition id:
• R194405
Years of experience:
• Early careers level with up to two years of experience (0-2 years of experience)
Company description
• Shell is a globally recognized energy company with activities across many countries, serving customers, businesses, and communities through energy solutions that support economic growth and daily living needs.
• The company operates across several business lines that span gas, power, chemicals, fuels, renewable energy solutions, and supporting digital and finance functions, bringing together teams of specialists in technology, engineering, analytics, commercial strategy, and operations.
• In India, Shell has a strong presence with large teams working in business operations, digital innovation, engineering support, research, and financial services, contributing to both national and global initiatives.
• Shell focuses on responsible growth with an emphasis on cleaner energy solutions, environmental responsibility, and smarter use of resources, while also creating opportunities for learning, collaboration, and career growth for its employees.
• The organization values honesty, integrity, and respect for people, encouraging an inclusive working culture where individuals are empowered to contribute ideas, build expertise, and grow in their careers.
• Employees are supported through training, structured development pathways, and exposure to international projects, enabling them to expand their professional capabilities.
• Shell promotes innovative thinking around energy transition, sustainable technologies, and digital transformation in operations, positioning itself as a leader in shaping future energy systems.
• With a large workforce in India, Shell plays an active role in local communities through education, skills and livelihood projects, startup incubation initiatives, and partnerships focused on environmental responsibility.
• The company believes people are central to success and places a strong focus on safety, ethical practices, customer satisfaction, and long term value creation for society.
• Shell is committed to inclusion, equal opportunities, and respect for diversity across gender, background, orientation, age, ability, and life experiences, seeking to create a workplace where every individual feels valued and supported.
Profile overview
• The role of Data Science Analyst focuses on supporting business units by applying analytical skills to process event data and helping create insights that inform business decisions and improvements in operational performance.
• The position is part of the Commercial Data Science team which works closely with process analysts, engineers, and experienced data scientists who collectively use data to understand how business processes run and how they can be improved through data driven methods.
• The analyst contributes to the Digital Process Twin portfolio, where digital representations of processes are built using event logs and process mining methods to observe how real world workflows behave across systems such as finance, sales, procurement, or customer service.
• In this role, the analyst prepares, cleans, and structures process event data from enterprise systems, ensuring that it is ready for modeling, visualization, and further study.
• Responsibilities include engaging in exploratory data analysis to identify trends, bottlenecks, waiting times, rework cycles, and other meaningful behaviors that affect process performance.
• The analyst assists in building dashboards and reports that communicate insights in a clear manner to stakeholders using tools such as Power BI or Tableau, helping teams see patterns and opportunities for improvement.
• The role provides exposure to creating features for analytical models, supporting the design of metrics related to performance, prediction, or anomaly detection, and learning how model outcomes support business decisions.
• The position also involves collaborating with cross functional teams and integrating data from various platforms such as SAP, ServiceNow, and Salesforce, thereby gaining familiarity with enterprise systems and operational contexts.
• Working in the Digital Process Twin Centre of Excellence allows the analyst to contribute to initiatives around process transformation, process mining, and responsible use of artificial intelligence, with a strong learning focus.
• The role suits individuals who enjoy working with data, learning new tools, thinking analytically about processes, and contributing to digital transformation in large scale business environments.
Qualifications
• Bachelor or Master degree in computer science, data science, engineering, mathematics, statistics, or any other quantitative discipline.
• Basic exposure to data analytics or data science tasks through academic projects, internships, or early professional roles.
• Working knowledge of Python and SQL for extracting, transforming, and analyzing data from different datasets.
• Familiarity with Python libraries such as pandas and NumPy for data manipulation and cleaning activities.
• Initial understanding of machine learning or statistical techniques applied to structured datasets or event logs, such as classification, regression, clustering, or descriptive statistics.
• Exposure to data visualization concepts and experience with tools such as Power BI, Tableau, Plotly Dash, Matplotlib, or Seaborn for charts and dashboards.
• Awareness of concepts related to event logs including case identifiers, timestamps, activities, and process paths, with interest in learning more about process mining techniques.
• Experience or academic exposure to tools like Celonis, SAP Signavio, PM4Py, or similar platforms is an advantage but not mandatory.
• Understanding of basic data engineering ideas including data quality, ETL workflows, pipeline creation, and ensuring consistency across integrated datasets.
• Strong analytical thinking, attention to detail, curiosity to ask questions of data, and willingness to learn from senior colleagues.
• Ability to work collaboratively in team settings, communicate findings clearly, and adapt to dynamic project requirements.
• Interest in learning about responsible artificial intelligence, interpretability of models, and ethical considerations when using analytical methods in enterprise settings.
• Awareness of process simulations, operations research concepts, or optimization methods through coursework or projects is beneficial.
• Openness to engaging with professional communities, technical forums, and learning networks to build skills and stay updated on emerging practices in data science and process analytics.
Additional info
• The role offers exposure to projects that directly influence business process performance, operational agility, customer experience, and financial outcomes, providing meaningful learning experiences early in one career.
• Shell provides structured training opportunities, online learning platforms, mentorship access, and rotation possibilities across teams to support employee growth in analytics, technology, and business knowledge.
• The working environment encourages honesty, respect, and integrity, creating a supportive culture where individuals are free to contribute opinions, share perspectives, and develop confidence in professional interactions.
• Employees are encouraged to find a healthy balance between professional commitments and personal priorities, with managers and teams supporting flexible approaches where feasible.
• The company is deeply committed to diversity and inclusion, supporting equal opportunities and striving to increase representation of women, persons with disabilities, and individuals from varied cultural and social backgrounds across all levels.
• Career paths can span multiple business lines including finance, integrated gas, renewable power, mobility, and digital services, giving analysts room to explore interests across energy and technology sectors.
• There are opportunities to engage in initiatives related to energy transition, sustainability, decarbonization efforts, and innovative energy solutions as Shell advances toward long term goals around lower emissions and cleaner energy systems.
• Shell India operates research and innovation centers in Bangalore and Chennai that work on advanced analytics, digitalization, engineering simulations, and process optimization, giving analysts access to experienced technical mentors.
• Employees benefit from participation in learning programs, leadership development, technical certification sponsorships, and community engagement projects.
• The company also invests in startup ecosystems and university partnerships across India, fostering innovation in energy, clean technology, electric mobility, and digital tools.
• Shell emphasizes strong ethical standards in recruitment and workplace practices, never charging fees for job applications and encouraging candidates to report suspicious requests.
• The organization maintains secure practices regarding personal data and follows clear policies for handling candidate information during the recruitment process.
• The role supports continuous development of transferable skills such as problem solving, data storytelling, stakeholder communication, and collaborative working.
• Successful candidates joining this role can expect to grow through exposure to cross cultural teams, international projects, and evolving digital technologies shaping the future of energy.
Key responsibilities of the role
• Prepare, clean, and transform process event data from different source systems to make it suitable for analysis and modeling activities.
• Perform exploratory data analysis to detect trends, repetitive patterns, waiting times, rework cycles, exceptions, and anomalies in process execution.
• Assist in building visualizations and dashboards that clearly communicate process insights to business users and leadership teams.
• Support senior data scientists in designing features, metrics, and process performance indicators that feed into predictive or diagnostic models.
• Work with engineers and analysts to maintain process data models, repositories, and pipelines that ensure accuracy and consistency of data over time.
• Contribute to initiatives where data from multiple systems such as SAP, Salesforce, and ServiceNow is combined to offer an end to end view of business processes across functions.
• Help prepare event logs for process mining activities and assist with studies conducted on platforms dedicated to process intelligence and execution management.
• Participate in documentation activities related to analytical models, scripts, dashboards, and process maps to support transparency and knowledge sharing.
• Support testing and quality assurance of analytical outputs to ensure reliability of dashboards, reports, and process insights being shared with stakeholders.
• Learn and apply ideas from responsible artificial intelligence and explainable artificial intelligence to ensure clarity in model outcomes and fairness considerations.
• Engage with process analysts and business stakeholders to understand questions they want answered through data and translate those questions into analytical tasks.
• Build an understanding of how finance processes, procurement flows, customer support interactions, or supply chain activities generate event data that can be studied.
• Contribute to discussions around process improvement opportunities by highlighting insights revealed through process mining or data visualization exercises.
• Stay curious about new tools, libraries, and methods emerging in data science and process analytics, and apply them under the guidance of experienced mentors.
Working environment and growth opportunities
• The role is located within modern office environments in Chennai and Bangalore with collaboration across global teams.
• Employees benefit from exposure to a multicultural setting where colleagues from different geographies work together on shared business objectives.
• There is a strong emphasis on safety, ethical conduct, compliance, and respect for colleagues in all interactions.
• The learning environment includes access to digital platforms, in person training, mentorship conversations, and communities of practice related to analytics and energy.
• Progression opportunities may involve taking on broader analytical responsibilities, leading process mining studies, or moving into specialist roles such as data scientist or process intelligence consultant.
• Shell encourages individuals to shape their own learning paths, exploring interests in areas such as automation, cloud data platforms, artificial intelligence, or business consulting.
• The organization supports employee wellbeing through programs focused on mental health, work life balance, ergonomic practices, and community building.
• Participation in social impact programs in education, livelihood, energy access, and innovation initiatives is encouraged, providing a sense of purpose beyond day to day work.
• Employees can engage in internal networks that support women in technology, accessibility and disability inclusion, cultural affinity groups, and early career talent development communities.
Please click here to apply.
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