Kroll is hiring for an entry level Data Scientist I role in India

Position

Data Scientist I

Company

Kroll

Location

Mumbai Metropolitan Region, India

Job Type

Full-time

Job Mode

Hybrid

Job Requisition ID

21014104

Years of Experience

1–3 years of practical data science or ML experience (internships, co-ops, research, and strong personal project work all count)

Company Description

Kroll operates as the world's premier independent institute focused on providing specialized risk, governance, financial advisory, and transparency solutions. With a rich legacy spanning nearly a century, the organization deploys proprietary data assets, cutting-edge software technology, and unique industry foresight to serve high-profile clients including global corporate entities, leading financial institutions, law enforcement bodies, and regulatory agencies. The global workforce comprises more than 6,500 dedicated professionals spread across worldwide jurisdictions, bound together by core commitments to operational excellence, corporate ambition, diversity, and social stewardship.

Operating with a strong emphasis on continuous career progression, environmental sustainability, and collaborative innovation, Kroll prioritizes empowering its workforce. Through specialized learning platforms, dedicated career advisory setups, and mentorship structures, employees are supported at every career milestone. Kroll operates as a certified CarbonNeutral entity while taking active roles in community building via the Kroll Charitable Foundation. The Enterprise Data Group inside Kroll drives internal digital transformation, machine learning deployment, product development, data governance, and generative AI integrations, giving technical teams direct exposure to real-world financial technology, automated workflows, and complex analytical systems.

Profile Overview

The Data Scientist I position located in the Mumbai Metropolitan Region represents a unique entry to early-career opportunity within Kroll's elite Enterprise Data Group. Designed specifically for ambitious analytics professionals with zero to three years of experience, this full-time hybrid post embeds practitioners into a multidisciplinary unit alongside highly accomplished data engineers, senior machine learning specialists, and business technology experts. The role provides an ideal learning environment to master every stage of the comprehensive machine learning lifecycle—from raw exploratory data analysis and data preprocessing to robust model building, automated feature engineering, deployment, and post-production monitoring.

In this position, the engineer plays a critical role in developing and scaling analytical solutions across diverse technology sectors, such as financial technology product innovation, corporate digital transformation, robotic process automation, business intelligence infrastructure, continuous data governance, and enterprise-grade generative artificial intelligence applications. The successful candidate will work extensively with cutting-edge cloud resources and modern computational platforms, primarily utilizing Databricks, PySpark, Delta Lake, and Microsoft Azure ecosystems (including Azure AI Foundry, Azure OpenAI, and Azure Functions).

Collaborating closely with senior practitioners and cross-functional corporate stakeholders, the Data Scientist I will translate complex, unstructured business problems into well-defined mathematical modeling frameworks and strategic analytical solutions. The day-to-day work requires writing clean, well-documented, unit-tested, and reproducible Python code while maintaining strict version control and experiment tracking metrics using frameworks such as MLflow.

Beyond core engineering obligations, the candidate will actively engage in advanced artificial intelligence paradigms, including prompt design optimization, Retrieval-Augmented Generation (RAG) architecture development, and intelligent multi-agent orchestration via frameworks like LangChain or LlamaIndex. By participating in peer code reviews, shared technical rituals, and continuous learning programs, the candidate contributes directly to Kroll's global mission—delivering absolute clarity and competitive advantages to clients navigating intricate governance, risk management, and valuation landscapes.

Qualifications

• Professional proficiency in writing robust, well-tested, maintainable, and clean Python code suitable for shared production software repositories and complex data science experiments.

• Hands-on experience or academic familiarity with core machine learning principles, predictive statistical modeling, natural language processing (NLP), and large language model (LLM) architectures.

• Basic understanding of data engineering concepts, including handling tabular datasets, conducting feature engineering workflows, and managing data pipelines using Databricks, PySpark, and Delta Lake.

• Awareness of cloud-based model deployment processes, cloud server management, and continuous monitoring systems within modern platforms such as Microsoft Azure, Azure AI Foundry, Azure OpenAI, or serverless Azure Functions.

• Exposure to generative AI frameworks and techniques, such as prompt engineering concepts, Retrieval-Augmented Generation (RAG) architectures, and orchestration frameworks like LangChain or LlamaIndex.

• Solid foundations in exploratory data analysis (EDA), data cleaning, statistical evaluation, hypothesis testing, and data mining methodologies.

• Familiarity with tracking machine learning experiments, tracking parameters, and logging model artifacts using toolsets such as MLflow.

• A Bachelor’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, Information Technology, or a closely related quantitative STEM field.

• Strong written and verbal communication skills, with an ability to clearly explain complex technical findings, mathematical concepts, and predictive insights to technical peers as well as non-technical stakeholders.

• Demonstrated problem-solving ability, attention to detail, and eagerness to proactively acquire new technology skill sets, explore emerging software tools, and read industry research.

• Ability to work effectively within a collaborative hybrid work environment, active participation in team rituals, peer code reviews, and cross-functional knowledge-sharing workshops.

Additional Info

• Growth & Mentorship: Every employee at Kroll receives a dedicated personal career advisor from day one to guide professional goals, supplemented by cross-service line mentorship programs involving global firm leadership.

• Continuous Learning: Employees gain full access to extensive learning ecosystems, including LinkedIn Learning platforms featuring thousands of specialized technical and professional courses.

• Hybrid Work Culture: The position provides a balanced hybrid working model based out of Kroll's modern office setup in the Mumbai Metropolitan Region.

• Work-Life Integration: Kroll supports holistic employee health and balance via global Employee Assistance Programs (EAPs) and various specialized Employee Resource Groups (ERGs).

• Environmental Responsibility: Over 70% of Kroll's global workforce operates within LEED or BREEAM certified green facilities, supporting Kroll's officially certified CarbonNeutral status aligned with UN Sustainable Development Goals.

• Social Impact & Philanthropy: The company actively drives social good through the Kroll Charitable Foundation and Kroll Cares initiative, providing 1:1 donation matching and supporting thousands of volunteer hours globally.

• Global Exposure: Opportunity to collaborate directly with cross-functional international teams serving major financial firms, regulatory authorities, global enterprise clients, and law enforcement agencies.

Please click here to apply.