Pradeep Singh

Lead ML Engineer

Gurugram, Haryana, India6 yrs 10 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

6+ years in machine learning and data engineering.
Expertise in building scalable data infrastructures.
Passionate about deploying reliable ML models.

Stackforce AI infers this person is a Data Engineering and MLOps specialist in the SaaS and Fintech sectors.

Contact

Skills

Core Skills

Data EngineeringMlopsMachine LearningData Analysis

Other Skills

PySparkPythonGCPLooker StudioBigQueryBootstrajQueryDOT NET MVCT-SQLSASData ValidationGenerative AI for LeadershipGenerative AILooker (Software)Continuous Integration and Continuous Delivery (CI/CD)

About

[Not looking for a job change anytime soon, but open to conversations] With 6+ years of experience in machine learning and data engineering, I specialize in building scalable data infrastructures and deploying reliable ML models into production. I bring hands-on expertise in GCP (BigQuery, Dataprep, Dataproc, Composer, GCS, Looker Studio), Python/PySpark, SQL, and Git. I’m passionate about streamlining data workflows and ensuring high-performing, production-grade models that deliver real-world impact. Outside of work, I'm a runner (HM PB: 2:19:07 | 10K PB: 59:12), sports enthusiast, and travel lover always looking for the next adventure.

Experience

6 yrs 10 mos

Total Experience

3 yrs 5 mos

Average Tenure

6 yrs 5 mos

Current Experience

Genpact

3 roles

Assistant Manager (MLOps)

Promoted

Sep 2022 – Present · 3 yrs 8 mos

𝟭. 𝗗𝗮𝘁𝗮 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 (𝘗𝘺𝘵𝘩𝘰𝘯, 𝘎𝘊𝘗):
🔹 Enhanced the data quality and integrity by implementing an automated report pipeline to compare base datasets with production data for each variable (numeric and categorical types).
🔹 Variable status indicators (Red, Green, or Yellow) are provided, offering clear visibility into data distribution drift.
𝟮. 𝗠𝗟 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 (𝘓𝘰𝘰𝘬𝘦𝘳 𝘚𝘵𝘶𝘥𝘪𝘰, 𝘉𝘪𝘨𝘲𝘶𝘦𝘳𝘺):
🔹 Developed a dashboard which consolidates various ML metrics and model performance reports into a single platform. It aids ML Engineers, the modelling team and LOBs in easily viewing these reports and making informed decisions.
🔹Integrated key metrics:
✅ Attribute Quality Status
✅ Model Performance
✅ Attribute Importance
🔹Resulted in enhanced data-driven decision-making capabilities.
𝟯. 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗿 𝗼𝗳 𝗖𝗿𝗲𝗱𝗶𝘁 𝗥𝗶𝘀𝗸 𝗪𝗲𝗯𝗔𝗽𝗽 (𝘉𝘰𝘰𝘵𝘴𝘵𝘳𝘢𝘱, 𝘫𝘘𝘶𝘦𝘳𝘺, 𝘋𝘖𝘛 𝘕𝘌𝘛 𝘔𝘝𝘊, 𝘛-𝘚𝘘𝘓):
🔹 Oversee the entire WebApp development cycle, from project scoping and timeline planning to developer coordination and issue resolution.
🔹 Co-develop the application as necessary to ensure timely progress.
🔹 Prioritize features based on stakeholder requirements and feedback.
🔹 Implement PD, LGD calculations, ORR, and LRR risk ratings.
🔹 Plan and execute the migration to a modern, open-source full-stack platform.