Experience

Nov 2020 - Present Lead Product Data Scientist at Anglo American

– Build the product from naïve stage to production stage from data science perspective which is deployed in 8 major mine sites of the company and one of them is largest platinum mine in
the world. Sailed through journey of customer- centric change management from AI as luxury item on shelf to necessity value added product for our users.
– Research and development of State-of-the-Art Machine Learning models for the product can assist Geologists in understanding and interpreting data in the exploration and operational
phase of mining.
– Building Generative AI (LLM + Vision models) capability (image to text to actionable insight) in the asset maintenance space that will reduce maintenance time, actionable procedures and
keeping in mind safety measures.
– Building Computer Vision based Video analytics framework that enables to understand safety features in the asset maintenance space and also understand tracking motion of machine
components in the processing space.
– Dealing with all stages of Data Science in the product, from Research to Production, in the Azure cloud platform.
– Collaborating with domain stakeholders, SMEs, engineering, and development teams to improve the product capabilities with a feedback mechanism while practicing the Scalable Agile
Framework (SAFe).
– Working closely with the Azure ML development team based in the USA to append and improvise data labelling capability as per our needs such that with minimal effort and to have high-
quality labelled data for our ML solutions.
– Designing and structuring complex pipelines that can lead to self-functioning data products with minimal maintenance, high efficiency, high optimisation, and optimistic Return on
Investment for business.
– Managing team of Data Scientists, Machine Learning Engineers, and Software developers to ensure they are getting the best from the experience and vice-versa, along with defining team
strategy, and data roadmaps.
– Accountable for identifying, embedding, promoting, and ensuring continuous improvement within the use of new data and advanced analytics across the organisation.
– Applied a disciplined and structured approach to project management, which includes rigorous scoping, planning, and execution phases, ensuring high-quality outcomes within budget and
timelines.
– Clearly communicate insights and technical approaches verbally and in writing, including documenting analytical methodologies and other outputs appropriate for use by specialists as
well as non-specialists.
– Facilitating build-vs-buy decisions on a vendor’s offering for Data Science solutions.
– Orchestrating the convergence of advanced research outputs from renowned institutions like CODES and CSIRO seamlessly integrate these insights into our products and ensures ongoing
relevance for our business.

Aug 2020 - Nov 2020 Data Scientist – Lead Consultant at Capgemini Invent

Jan 2019 - July 2020 Data Scientist at MMG Ltd., Innovation - Dept.

– Led the development of a comprehensive discovery service leveraging geolocated real-time drilling data, press releases, and financial insights from global exploration industries,
enabling efficient identification and evaluation of new opportunities for partnership. Designed and implemented of a robust data warehouse, schedule based ETL data
pipeline, information retrieval models and dynamic dashboards using Dash.
– Developed and executed strategic initiatives that transformed AI from an ancillary tool to a core component of business operations, driving a measurable increase in ROI.
– Optimized data pipelines and infrastructure in the Azure cloud platform, ensuring high efficiency and ROI.
– Collaborated with stakeholders to align data science projects with business goals, successfully translating technical solutions into business value.
– Championed cross-functional collaborations that bridged data science and operational teams, leading to a 20% improvement in data-driven decision-making processes.
– Designed and developed an advanced geoscience data analysis services integrating AI and digital logging capabilities for consistent lithology logging, sulfide mineralization detection,
and rock quality designation (RQD) assessment, featuring interactive tools for depth correction and data export. That involves research to production of sequential classification and
regression models and computer vision models like segmentation, detection, autoencoders and classification.

June 2019 - Nov 2019 Nature Language Processing Researcher at Monash University - Dialogue Research Lab

– Research and development on sequence-to-sequence autoencoders using transformers for the Dialogue Agent (SIRI like Virtual assistant) for car drivers sponsored by Toyota under Prof.
Phil Cohen’s research team.
– Research paper discussion and implementing State of The Art models in the Natural Language Processing for Dialogue Research.
– Implementation and evaluation of the project: Natural language generation from logical form (Graph).

Aug 2017 - July 2018 Research Engineer - Data Engineer at Indian Institute of Technology, FOSSEE Dept

– Analysed the current architecture and problem of the project and proposed “IoT Enabled Virtual Lab” and then designed. Developed software for IoT enabled improved solution, which
reduced the cost to ~48% & made it more scalable architecture.
– Fault Detection in IoT Remote Lab systems using Machine Learning and logged data.

June 2016 - May 2017 Software Engineer - Data Analyst at Eduvance, R&D IoT Dept.

– Worked on designing, developing, and testing software and hardware of IoT products related to Smart Home Automation, Smart City, Inventory Management, Warehouse Management and
Agriculture System.
– Creating Data Pipeline for IoT Sensors data from collection to wrangling to transforming to Interactive Dashboards in Plotly.
– Developed Grad-me (Auto-Grader – Skill Assessment Platform) for ARM 7 and Image Processing [Python, Django]
– Performed from product development from hardware to software to data to AI layers.
– Instructor for Industrial training courses on IoT and Data Science.