, India

Job Family Group:

Research and Development

Worker Type:

Regular

Posting Start Date:

January 22, 2026

Business Unit:

Finance

Experience Level:

Experienced Professionals

Job Description:

What's the role

As a Senior Data Scientist within the Digital Process Twin (DPT) portfolio, you will lead the end-to-end technical design and build of process-centric ML/AI solutions-owning runtime reliability and reusable assets as a individual contributor. You will apply process mining, optimization, and AI/ML techniques to process-centric data to identify inefficiencies, predict process behavior, and optimize end-to-end business performance. You will collaborate closely with engineers, architects, and fellow data scientists to design scalable analytical solutions and integrate them into Shell's process-mining ecosystem.

The Digital Process Twin Centre of Excellence (CoE) aims to "Empower Process Transformation through Digital Process Twins" by advancing process-mining and analytics capabilities. Shell is recognized as an industry thought leader in process intelligence, pioneering innovative analytical methodologies and data-driven process transformation. The CoE collaborates with academic institutions, industry forums, and technology vendors to drive innovation and applied research in process analytics.

If you are passionate about building advanced analytical models using process event data and developing intelligent solutions that enhance operational agility and enable autonomous processes, we invite you to join us as a Senior Data Scientist driving Shell's digital process transformation journey.

What you'll be doing

• Own the technical architecture and reusable design patterns for analytical solutions - including discovery/ideation workshops with business stakeholders - from problem framing and data design to deployment and run operations.
• Define canonical process-data models and event-data standards; build versioned, reusable pipelines (with case IDs, activities, timestamps, attributes) from SAP, Salesforce, ServiceNow, etc.
• Apply process-mining to discover patterns and root causes; engineer features from event logs and quantify improvement opportunities against target KPIs.
• Build and productionize ML/OR models on process event data (classification, anomaly detection, forecasting, prescriptive optimization) to enhance business-process performance.
• Implement and enforce MLOps standards-CI/CD, versioning, automated tests (leakage/drift/fairness), model registry, and observability-with defined SLOs and rollback/playbooks; embed RAI/XAI by default, and ensure these standards are adopted consistently by Data Scientists across projects.
• Collaborate with data engineers and software developers to embed and scale models in Shell's process-mining platform for reliable, near-real-time analytics.
• Establish evaluation frameworks and a quality bar-offline benchmarks, shadow/canary runs, A/B or interleaving tests, and drift monitoring-tied to business KPIs (e.g., cycle time, STP%, backlog, rework).
• Collaborate with academic and industry partners (vendors, startups, open-source communities) to bring external perspectives, co-develop prototypes, and translate research into production (PoCs → benchmarks → deployment).
• Act as technical SME and raise the team's technical bar via design reviews, code reviews, pair-programming, coding exercises/workshops, and learning sessions.

What you bring

• 8-10 years in applied data science/ML/OR, including ≥2 years with process/event or behavioral data at enterprise scale.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related quantitative field.
• End-to-end production delivery record: shipped ≥3 production ML/OR solutions from design to stable run (CI/CD, versioning, observability) with defined Service Level Objectives (SLOs), demonstrating KPI uplift, and executing safe release/rollback procedures; embedded Responsible/Explainable AI (RAI/XAI).
• Applied ML/AI & OR algorithms: hands-on with supervised/unsupervised learning (classification, clustering), time-series forecasting, anomaly detection, graph/process-mining methods, and prescriptive optimization/simulation; strong model selection & trade-off reasoning (features, evaluation, cost-of-error).
• Process-data modeling & standards: canonical event/process schemas, schema/versioning & data-quality standards (lineage, validation, freshness), and governed, reusable pipelines/feature sets; experience with schema evolution and late events.
• Platforms & packaging: integrated models with Celonis/Signavio (or equivalent) and open-source tooling (e.g., PM4Py/ProM); packaged solutions as services/components adopted by other teams.
• Performance & reliability: optimized cost/latency/throughput (profiling, vectorization, caching); built runbooks and dashboards that reduced Mean Time To Recovery (MTTR) and prevented regressions.
• Research → production (with academia): led PoCs → benchmarks → deployment with academic partners; reproduced state-of-the-art (SOTA) results and translated them into maintainable production systems.
• Technical influence as a senior IC: raised the team's technical bar via design/code reviews, pair-programming, coding exercises/workshops, and learning sessions; improved test coverage, reuse, and documentation.
• Rapid prototyping & incubation: turn new ideas into quick, decision-quality prototypes; design baselines, A/B or interleaving tests where relevant, and drive a build/kill/iterate path based on impact and cost.

Must have Skills:

• Python & SQL, production-grade code (tests, packaging, git).
• Process/event data modeling & process mining (discovery, conformance, enhancement; features from event logs).
• Applied ML/AI & OR: supervised/unsupervised, time-series, anomaly detection, graph/process-mining, prescriptive optimization.
• MLOps in practice: CI/CD, containers, experiment tracking & model registry, monitoring/observability with SLOs, safe release/rollback, RAI/XAI.
• Technical leadership as a senior IC: lead design/code reviews, mentor data scientists, co-design with DE/PM/PO, run discovery/ideation workshops, and document decisions clearly.
• Cloud & data platforms: Azure/AWS/GCP; Spark/Databricks (incl. jobs/orchestration exposure).
• Platform integration: embed models into Celonis/Signavio (or equivalent) for near-real-time analytics.
• Performance engineering: profiling, vectorization, caching; cost/latency/throughput tuning.
• Tech transfer & enablement: collaborate with academic/industry partners; coach via pair-programming and coding exercises/workshops.
• Decision narratives for executives: translate experiments and model performance into clear recommendations with risks, trade-offs, and expected impact; build decision-ready dashboards/briefs.

Nice have Skills:

• Open-source process-mining & feature/graph stores (PM4Py, ProM, Feast, Neo4j).
• Change leadership & training: playbooks, brown-bags, reusable templates that scale practices across teams.
• Community impact: publications/patents or meaningful open-source contributions in process intelligence/applied AI.

Key Competencies required for this role:

• Applied Data Science Expertise
• Analytical Solution Architecture
• Technical Leadership

What we offer

You bring your skills and experience to Shell and in return you work with talented, committed people on one of the most important challenges facing our planet. You'll have the opportunity to develop the skills you need to grow in an environment where we value honesty, integrity, and respect for one another. You'll be able to balance your priorities as you become the best version of yourself.

• Progress as a person as we work on the energy transition together.
• Continuously grow the transferable skills you need to get ahead.
• Work at the forefront of technology, trends, and practices.
• Collaborate with experienced colleagues with unique expertise.
• Achieve your balance in a values-led culture that encourages you to be the best version of yourself.
• Join an organisation working to become one of the most diverse and inclusive in the world. We strongly encourage applicants of all genders, ages, ethnicities, cultures, abilities, sexual orientation, and life experiences to apply.
• Grow as you progress through diverse career opportunities in national and
• international teams.
• Gain access to a wide range of training and development programmes.

An Inclusive & Progressive Place to Work

• To power progress together, we need to attract and develop the brightest minds and make sure every voice is heard. Here are just some of the ways we're nurturing an inclusive environment - one where you can express your ideas, extend your skills, and reach your potential.
• We're creating a space where people with disabilities can excel through transparent recruitment process, workplace adjustments and ongoing support in their roles. Feel free to let us know about your circumstances when you apply, and we'll take it from there.
• We're closing the gender gap - whether that's through action on equal pay or by enabling more women to reach senior roles in engineering and technology.
• We're striving to be a pioneer of an inclusive and diverse workplace, promoting equality for employees regardless of sexual orientation or gender identity.

Shell in India

Shell is a diversified energy company in India with 13,000 employees, and presence in Integrated Gas, Downstream, Power, Renewable and Upstream. Additionally, we have deep capabilities in R&D, digitalisation, and business operations.

Our global strategy, Powering Progress, is designed to generate value for our shareholders, customers, and the wider society, and focuses on creating more value with less emissions. The strategy supports our purpose of providing more and cleaner energy solutions, with the aim of profitably transforming Shell into a net-zero emissions energy business by 2050. As India moves towards its target of net-zero emissions by 2070, Shell India aims to play a leading role in securing vital energy for today, while investing in, and helping to build, the energy system of the future through strategic investments in the country.

Our Lubricants business serves over 50,000 consumers through a strong network of over 200 distributors, and operates an end-to-end value chain that spans conceptualization, development, and production at a world-class blending plant at Taloja. Through our 350-plus retail stations, we offer an integrated mobility experience including fuels, cafes, and convenience stores, with a prominent network of EV recharging facilities.

Shell owns and operates a LNG re-gasification terminal at Hazira, Surat, with a capacity of 5 MTPA and a LNG truck-loading unit that plays a crucial role in helping meet India's growing demand for gas across sectors. In 2022, Shell acquired Sprng Energy in a $1.55 billion deal to build an integrated energy transition business in the country. Sprng is a leading renewable energy company in India which develops and manages solar, wind, and hybrid power generation facilities and infrastructure.

Our three capability centres across Bangalore and Chennai serve as a technology and innovation powerhouse for Shell globally, working as a delivery engine for core technical, digital, and finance processes: pioneering digital innovation and cutting-edge technologies across the energy sector. We also have strong academic partnerships and collaborations with leading universities and technology institutes to accelerate decarbonization efforts within the energy sector.

We are committed to positively contributing to the communities in which we operate through programmes on STEM Education, Skilling, and Livelihood across India. We nurture and invest in startups developing initiatives focused on accelerating energy innovation through programs such as Shell E4 and Shell Eco-marathon. We also have strategic investments in new energy companies such as Husk Power, d.light, Orb Energy, and Cleantech Solar.

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