Pune, Chennai · Hybrid

Consultant, Data Science and Analytics(Credit Risk)

Full-timePosted 4 Nov

Salary: ₹27.2–30.1 LPAEstimated from AmbitionBox data for this role at TransUnion. The employer has not stated pay.
Experience: 5 years
Eligible batches: 2021
Degree: Master's
Location: Pune, ChennaiHybrid
Apply by: 9 Nov 2026

About the role

TransUnion is looking for a Consultant in Data Science and Analytics focused on credit risk. The hybrid role blends virtual work with on‑site collaboration at the Pune or Chennai office, delivering predictive and prescriptive insights to lenders in the U.S. short‑term lending market.

Responsibilities

Lead client engagements that apply segmentation, logistic regression, machine‑learning and scenario analysis.
Produce clear, data‑driven presentations for internal and external stakeholders.
Collaborate with sales, product and analytics teams to uncover growth opportunities and improve risk management.
Develop and maintain models, monitoring tools and large‑scale data pipelines using R, Python, SQL, Spark and cloud platforms.
Mentor junior analysts and oversee multiple initiatives with limited supervision.
Stay abreast of emerging analytical techniques and technologies to drive continuous innovation.

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Eligibility

Master’s degree in statistics, applied mathematics, financial mathematics, operations research or a related quantitative discipline.
Minimum five years of professional experience in advanced analytics within financial services, consumer credit or a similar industry.
Strong understanding of consumer lending, credit risk management and credit bureau data.
Excellent communication skills and ability to influence at all organizational levels.
Proven project‑management capability in fast‑paced, matrixed environments.

Skills

Proficiency in R, Python, SQL and Spark.
Experience building predictive models, logistic regression and segmentation analyses.
Knowledge of cloud‑based data platforms.
Ability to translate complex analytics into actionable business recommendations.
Mentoring and team‑leadership experience.

Resume keywords

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R
Python
SQL
Spark
Machine learning
Logistic regression
Segmentation
Predictive modeling
Statistical modeling
Credit risk

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Benefits

Work‑life flexibility with a hybrid schedule (minimum two days on‑site per week).
Opportunities for professional growth within a global data‑science organization.
Access to cutting‑edge technology and collaborative cross‑functional projects.

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