Citizen Data Science Specialist

About us

For well over a century, ExxonMobil has been at the heart of creating and growing a modern world. We embrace the power and promise of technology, pushing the boundaries of what's possible. For billions around the world, lives are better and last longer because of the innovative problem solving and reliable energy we provide. And when it comes to developing industrial solutions to reduce carbon emissions, ExxonMobil is truly the leader.

We don't stop at "good enough." We are committed to doing what's right, even if it's difficult or unpopular. We hold ourselves to high standards, challenge what's possible and invest in innovation to meet society's critical needs.

Real change begins with bold questions, drive, and ambition. Here, your talent, determination and contributions shape how far you'll go and the impact you'll make along the way.

Our future success depends on exceptional people. We invest in developing talent through meaningful work, challenging assignments, mentorship, and experiences that help build the next generation of leaders.

Our Culture

We are uniquely ExxonMobil. Integrity, care, excellence, resilience and courage, these core values determine how we work every day. At ExxonMobil, our values aren't just words— they're how we show up, focused on delivering the right answer, the right way, every day.

What role you will play in our team:

We are seeking a Citizen Data Science SME to lead the development and scaling of enterprise-wide standards, governance, and best practices for low-code and AutoML-driven analytics.

This role will act as a strategic enabler and technical authority, responsible for building a robust Citizen Data Science capability across the organization. The SME will drive adoption of low-code analytics platforms, establish reusable frameworks, and ensure delivery of high-quality, scalable, and governed analytical solutions.

The role will partner closely with business, data engineering, IT, and vendor teams to incubate new analytics capabilities, lead proof-of-concept (POC) initiatives, and upskill a growing community of Citizen Data Scientists.

The role will be based in Bengaluru, Whitefield and is a full-time office-based position.

What you will do

Key Responsibilities:

Evaluating Business Processes: Identifying opportunities for automation to improve efficiency and effectiveness.

Define and implement enterprise standards, best practices, and governance frameworks for Citizen Data Science

Lead tooling strategy and platform adoption (e.g., Dataiku, Alteryx, Power Platform, AutoML tools)

Drive and oversee POCs, pilots, and vendor incubation projects to evaluate and scale new capabilities

Develop reusable templates, workflows, and accelerators for low-code analytics

Establish model lifecycle practices (development, validation, deployment, monitoring) within low-code platforms

Train, mentor, and upskill Citizen Data Scientists across business units

Partner with data engineering and IT to ensure integration, scalability, and compliance

Act as a bridge between business and technical teams, translating use cases into actionable analytics solutions

About You

Required Skills and Qualifications:

Core Technical Skills

Strong experience with low-code/no-code data science platforms: (e.g. Dataiku, Alteryx, KNIME, Power Platform, or similar)

Familiarity with AutoML and model development concepts

Data preparation, transformation, and feature engineering

Understanding of ML lifecycle (MLOps concepts in low-code context)

SQL proficiency (required); Python/R (working knowledge preferred but not mandatory)

Data & Analytics Skills:

Predictive modeling, forecasting, segmentation, and optimization

Data visualization tools (Power BI, Tableau)

Data pipeline and workflow automation

Governance & Framework Design:

Experience defining: Best practices, Reusable frameworks, Model governance standards

Risk and compliance guardrails

Soft / Leadership Skills:

Strong stakeholder management and influencing skills

Ability to train and enable non-technical users

Strategic thinking with execution focus

Excellent communication: translating complex analytics into business value

Preferred Skills & Qualifications:

Experience building or scaling a Citizen Data Science program or CoE

Prior experience with enterprise data governance, model risk management, or regulated environments

Exposure to cloud ecosystems (Azure, AWS, GCP) and their ML/analytics services

Experience integrating low-code solutions into production pipelines

Background in training, curriculum development, or community enablement

Knowledge of MLOps, Responsible AI, and model monitoring practices

Consulting or strategy experience in analytics transformation initiatives

Pandas and scikit-learn, XGBoost / LightGBM, PyTorch or TensorFlow for advanced use cases, Azure ML and Azure Databricks / Spark, MLOps

Build machine learning models in Python using popular machine learning libraries NumPy & scikit-learn

Build & train supervised machine learning models for prediction & binary classification tasks, including linear regression & logistic regression

Python, scikit-learn (Classical ML), PyTorch, TensorFlow (Deep Neural networks) (Libraries inside the python), Databricks, and Spark

Has personally developed a predictive model/advanced analytics model evaluation metrics like regression, timeseries, forecasting etc.

Strong SQL experience, Power BI or equivalent visualization experience

Has developed AI/ML solutions

Job Group Capability

Data Science, Digital & Analytics

Functional Skills

Machine Learning

Data Visualization

Data Architecture & Strategy

Applied Software Engineering for Data

Data Integration

Data Modeling

Data Management

Alternate Location:

Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship.

Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.