Data Scientist III

S&P Global

Data Scientist III building data products using AI/ML for operational efficiency and data insights. Collaborating with teams and stakeholders in a data-driven environment.

Posted 6/12/2026full-timeGurugram • 🇮🇳 IndiaSeniorLeadWebsite

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformMicroservicesSpark

About the role

Key responsibilities & impact

Architect data lake/lakehouse platforms for forecasting, anomaly detection, and BI/analytics using Databricks, Spark, and Delta-style patterns.
Set and enforce engineering standards for data modeling, integration, and pipeline design across teams/products.
Lead cloud event-driven/microservices architecture that integrates with web front ends and APIs.
Design, build, and optimize batch and event-driven ELT/ETL pipelines for analytical and operational workloads.
Build ingestion/transformation flows aligned to bronze/silver/gold, with validation, CI/CD, testing, and observability baked in.
Implement scalable time-series forecasting training and inference across categories.
Build model monitoring (RMSE/MAE/bias/coverage/residuals) with dashboards and automated alerts.
Develop residual/outlier detection using Z-scores, PELT change points, and confidence-interval breach checks.
Implement classification/risk-scoring models (e.g., Logistic Regression, Random Forest, XGBoost, clustering, HMMs) for anomaly classification and category risk.
Automate data quality and schema validation (missing dates/targets, type changes, schema evolution, allocation shifts).
Detect drift in data and model behavior (e.g., allocation stability, category mix changes).
Deliver per-category anomaly flags and summarized insights for decision-makers.
Provide technical leadership (code/design reviews, mentoring, knowledge sharing) for engineers and data scientists.
Collaborate with product/UX/business to refine requirements, prioritize work, and plan roadmaps.
Champion engineering excellence: quality, performance, and operational readiness.

Requirements

What you’ll need

Typically, you’ll bring 7+ years of experience in data engineering, Machine Learning and building production-grade data pipelines and platforms in a cloud environment.
A Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related field is required; a Master’s degree is a plus.
Preferred qualifications include experience with Databricks/Spark and lakehouse architectures, along with relevant cloud certifications (e.g., Azure/AWS/GCP data engineering) or Databricks certifications.

Benefits

Comp & perks

Health & Wellness: Health care coverage designed for the mind and body.
Flexible Downtime: Generous time off helps keep you energized for your time on.
Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in-class benefits for families.
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data lakelakehouse architectureforecastinganomaly detectiondata modelingELTETLmachine learningclassification modelsdata quality

Soft Skills

technical leadershipmentoringcollaborationknowledge sharingengineering excellence

Certifications

Databricks certificationcloud data engineering certification