Nov 2022 – Sep 2024 · 1 yr 10 mos · Gurugram, Haryana, India

• Client Engagements :
• Oil & Gas : Fleet Sizing optimisation solution, reducing the OPEX by 30+Mn/year
• Oil & Gas : Value Chain Forecasting of Polyethylene Business.
• Lifesciences : Total Commercial Spend optimisation for commercial arm with sales uplift on > 25%.
• Metal Manufacturing : Led and developed, a solution for tracking anodes in aluminium plant for a quality check and assurance use case.
• Research & Development
• Data Synthesiser : A python package, to generate mimicry of real world dataset using Bayesian Networks to learn not just feature level distribution, but also intra-feature distribution.
• Transaction Analytics : A transaction analytics product, to process, categorise transactions in banks; Empowering downstream use cases - for ex : Anomaly Detection.

Jan 2022 – Nov 2022 · 10 mos · Gurugram, Haryana, India

• Client Engagements :
• FIG Practice : Developed Credit Risk Models for NBFC and Banks, across segments such as MSME, Retail Loans; Improving the GINI by 40+ %.
• FIG Practice : Contributed in streamlining, digitising the underwriting process of the clients.
• Research & Development
• PySlice : A python asset to reduce the development of credit risk models from 4 months to less than 1 month;
• QBicK : A python package, easy to use api for quantum computing implementation of classical machine learning algos such as SVM, Spectral Clustering etc.

Jan 2022 – Sep 2024 · 2 yrs 8 mos · Gurugram, Haryana, India · On-site

• Industries I worked - Metal Manufacturing, Life Science,Banks, NBFC, Oil & Gas.
• Worked across South East Asia, LATAM & Middle East geographies.

Jul 2020 – Jan 2022 · 1 yr 6 mos · New Delhi, Delhi, India · On-site

• Here is where I learned to manage a small team of Jr DS’s and a team of Annotators.
• Developed Computer Vision solutions to bring down the TAT and OPEX of our ground operations. Developed Novel OCR systems to extract text from natural images, implementing few research papers. Contributed to multiple in-house assets (like PIP packages) around deep learning models (when pre-built frameworks such as PyTorch lightning etc were not that huge) from data ingestion to model monitoring and a small script to dockerize and deploy light weight models.

Aug 2018 – Jun 2020 · 1 yr 10 mos · Thiruvananthapuram Taluk, India · On-site

• Learned the ropes of data science here.
• Worked in Core Data Science & Innovation CoE. In core data science, built the Retail & Demand Forecasting models for NNA and Japan market across various models leveraging internal as well as external sources, optimising inventory and reducing OPEX, Predictive maintenance for the shop floor of motors to lower the incidence rates etc. In the innovation verticals, designed and implemented prototypes across - Customer Experience enhancement - how customers were interacting with Kiosks, Product Planning Tool to bring down the TAT in planning process etc.

Jun 2017 – Aug 2017 · 2 mos · Gurugram, Haryana, India · On-site

• My first big corporate exposure. Mapped to the IT Risk Advisory Team, collecting data of various firms of interest and building an App on top of the same.

Jun 2016 – Aug 2016 · 2 mos · Noida, Uttar Pradesh, India · On-site

• My first startup stint, learned about swift programming and iOS app development.

Jul 2015 – Jul 2015 · 0 mo · India · On-site

• My “office” was in an underground control station in a basin surrounded by mountains on three fronts and the tail race from the Chamera Dam on the fourth. Shadowed few brilliant electrical engineers, learned a bit about PLC based online data monitoring systems & big turbines which generate hydroelectricity from them.