Data Scientist III

S&P Global

Data Scientist III role in S&P Global building data products using AI/ML. Collaborating with internal teams to enhance operational efficiency and financial outcomes.

Posted 7/16/2026full-timeGurugram • 🇮🇳 IndiaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting data lake/lakehouse platforms, building scalable data pipelines, and implementing machine learning models in cloud environments. Proficient in data modeling, ETL/ELT processes, and ensuring data quality and validation.

Highest-signal resume keywords

Data EngineeringMachine LearningDatabricksPythonSQL

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentETL/ELT ProcessesData ModelingTime-Series ForecastingAnomaly DetectionClassification ModelsPerformance TuningBatch ProcessingEvent-Driven ArchitectureMicroservices Design

Tools & Technologies

DatabricksSparkDelta LakeCI/CDAPIsRESTGRPCCloud Platforms

Certifications & Qualifications

Azure Data EngineeringAWS Data EngineeringGCP Data EngineeringDatabricks Certification

Industry Keywords

Data LakeLakehouse ArchitectureDimensional ModelsStar SchemaSnowflake SchemaMedallion DesignEvent BusesServerless TriggersRMSEMAE

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformGRPCMicroservicesPySparkPythonSparkSQL

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).

Requirements

What you’ll need

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.
Expert SQL (complex joins, window functions, performance tuning at scale).
Strong Python for data processing, APIs/microservices, and analytics.
Hands-on PySpark for large-scale distributed processing and ETL/ELT.
Solid data modeling (dimensional models, star/snowflake schemas, medallion design).
Proven Databricks experience (notebooks, jobs, clusters, Delta tables) and lakehouse architectures.
Strong grasp of cloud-native, event-driven architectures (queues, event buses, serverless triggers) for data/ML workflows.
Experience designing/operating microservices exposing REST/gRPC APIs for forecasting and analytics.
Hands-on, production experience with time-series forecasting (ARIMA or similar).

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.