Ramesht Shukla Email & Phone Number

Singapore

Singapore

Singapore

Key Responsibilities:- Lead the initiative to enhance and automate the capabilities of machine learning infrastructure using Docker, Kubernetes, and Terraform.- Provide crucial support to data science and machine learning teams.- Collaborate with data scientists and research engineers to ensure meticulous design and seamless functioning of code.- Spearhead MLOps initiatives to enhance the productivity of the data and machine learning teams, facilitating seamless deployments of models, ensuring easy maintenance, and keeping cloud costs within budget.Working With: AWS (SageMaker, S3, ECS, EKS, etc.), Python, Expectations, Docker, Kubernetes, Jenkins, Airflow, GitLab(Builds, Pipelines, runners, pakages), bash, Terraform

Singapore

As Data Scientist in Grab's fraud-security and transport team, I worked on the intersection of big-data engineering, real-time analytics, and behavioral modeling to drive value business value and reduce user and partner friction on the platform.I balanced hands-on model development while collaborating cross-functionally with my stakeholders across Grab.- Refactored one of the key fraud detection MO machine learning pipelines (Python, Pyspark, SQL, and Scala) in production for better code readability and performance. Reduced memory usage and runtime by 20% via data type optimization and caching. Also, added some new actioning rules over to increase its performance.- Collaborated with stakeholders from various grab tech families to identify their specific requirements and implemented the necessary changes to one of the key machine learning pipelines to better serve our end users.- Proposed and implemented good coding practices such as code documentation, library packaging, versioning, and containerization.

Singapore

As a Data science Intern, I worked closely at the intersection of Big-data engineering and Machine learning engineering, real time data analytics and Geospatial analytics to drive the business value from door step food delivery.I worked with the grab's data science geo team in building and deploying some of the key state-of-the-art features that will impact 180+ million users using doorstep food delivery service.- Refactored multiple ML pipelines using PySpark and SQL to speed up the pre-processing of petabytes of real time geo-location data.- Helped in coordination and system design for the A/B testing for deployment of features in South-East Asia and optimised the existing ML pipelines for better performance in next round of A/B tests.- Helped in designing the destination preview feature for nearby places; A Hackathon idea that was patented.For Master's thesis project :I am working on creating SDK for LIDAR data ingestion and processing for in-house services using state-of-the-art and data driven approaches for 3d object detection and depth perception.

California, United States

London, England, United Kingdom

London, England, United Kingdom

OpenMined is an open-source community whose goal is to make the world more privacy-preserving by lowering the barrier-to-entry to private AI technologies.

Singapore

• Perform data collection form test participants.• Managing and developing a data preprocessing and analysis pipeline to extract useful information form raw sensor data and convert it to actionable data.• Creating reports and analysis documentation for industry partner.

Indore, Madhya Pradesh, India

• Researched on condition monitoring methodologies for rotating components in mechanical systems and successfully created supervised machine models with accuracy of 98%. • Worked (alongside Research scholars) to assess on novel end to end mechanical (Polymer gears and Hydraulic telescopic Cylinders) and bio-medical applications (Root Canal Kinematics) of machine learning and deep learning and implemented them using MATLAB and Python.• Collaborated with Research Scholars and Advisor for taking a lecture on “Application of Python and Machine Learning in Mechanical Systems” during a short-term course with over 50 participants.

Singapore

• Completed a 4 Week Intense training program in “Big Data Analytics using Artificial Neural Networks.”• Undertook a 1 Week program conducted by HPE on “Big Data and Hadoop System Administration.”• Analyzed, preprocessed, and created a regression model for predicting electricity bill using the yearly electricity consumption data and achieved an R-Score of 0.95. R and Python were used for plotting visualizations and making prediction models.

Master Of Computing

Relevant coursework : Data driven decision making, Big data processing and analytics, Functional and stream programming, Knowledge.

Bachelor Of Technology, Electronics Engineering, 9.3/10

Activities and Societies: Co-Founder and core team lead of Mozilla Campus club. Member of Core Technical Team at Network Security Group..

Diploma In Network Security