Shashank Singh

Roles & Responsibilities:

• Created different models for maximum coverage of detections and deployed in client(light weight, Random Forest) and cloud(full, XGBoost) for Endpoint Detection(XDR/EDR).
• Created models for Malware detection,DNS tunneling, data theft and other use cases in NDR/EDR.
• Applied improvised sampling technique which reduced sample size from trillions of samples to 7-16M samples for training.
• Reduced time for model building and deployment by making automated model (re-)training and deployment, i.e. MLOps, using MLFlow/ Amazon Sagemaker from 5 weeks to 4 days.
• Solved and handled existing FPs and model performance issues by feature engineering. Analyzed and removed features which are skewed towards one class.
• Evaluated emerging technologies(LLM) and assess potential applications within organization's infrastructure and future projects.
• Coached and mentored junior data scientists on Data Science and feature engineering techniques.
• Lead 3 data scientists and 2 software engineers.

Achievements:

• Reduced company's cost and time in re-training models which resulted in $2M dollars save.
• Enhanced model efficacy for 40,000 customers by reducing FPs with better models.

Roles & Responsibilities:

• Gathering, cleaning and analyzing data from different sources by collaborating with stakeholders.
• Created Models for classifying rules and scripts required to complete investigations in Python(Random Forest)
• Improved existing algorithm by fine tuning and creating algorithm for prioritizing tenants based on priorities to get processed.

Achievements:

• Helped company to increase PSAT scores by 1.3 by analyzing major issues and concerns from clients.

Roles & Responsibilities:

• Created Models for classifying non categorized transactions in bank's account statement such as salary, EMI, credit etc. in Python.
• Lead and mentored junior data scientists on modelling.

Achievements:

• Company got few Fin-tech/banking projects based on POC done on bank's statements

Role and Responsibilities:

• Created Models for getting future amount of items and cost to buyer and supplier (construction domain) by implementing Machine Learning(linear regression, Random Forest and ARIMA).
• Created dashboard using tableau to show changes in price for raw materials region wise.
• Lead team for creating end to end POC and making it to production.

Achievements:

• 16% growth of product in sales for company

Role and Responsibilities:

• Created reports and dashboard for presenting to management.
• Worked with different teams(Content and Search) and applied machine learning/data science in retail specific domain Analyzed and gained insights from data.
• Worked in (NLP) to get Canonical Brand of specified brand as Named Entity Recognition(NER) for third party content to use in 'Search'

Achievements:

• Increased organization's product growth by 14%.

Role and Responsibilities:

• Enhanced loan and ledger web page for GE Capitals by using spring batch and automated flow of approvers.