Rajesh Kalal

AI Researcher

Mumbai, Maharashtra, India4 yrs 1 mo experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Led deployment of machine learning models boosting revenue.
Engineered recommendation systems improving efficiency by 48%.
Enhanced data analysis processes with advanced AI techniques.

Stackforce AI infers this person is a Data Scientist specializing in SaaS and machine learning solutions.

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Skills

Core Skills

Machine LearningData EngineeringData Analysis

Other Skills

AWS RedshiftAmazon RedshiftAmazon Web Services (AWS)AzureCascading Style Sheets (CSS)DashboardsGoogle Analytics StudioGoogle analytics studioGraphsHTMLHTML5IntelliJ IDEAJavaScriptLangChainLinux

About

Experienced and innovative Data Scientist with strong mathematical skills and comprehensive knowledge of machine learning evaluation metrics and best practices. Nearly three years of experience developing programs and algorithms that enable autonomous machine actions while managing large-scale client projects. Expertise in predictive analysis, model creation, model deployment, and computational statistics to develop advanced AI models addressing complex problems in natural language processing, and machine learning domains.

Experience

4 yrs 1 mo

Total Experience

2 yrs

Average Tenure

3 yrs 9 mos

Current Experience

Hansa cequity

3 roles

Senior Data Scientist

Aug 2025 – Present · 10 mos · Mumbai, Maharashtra, India

Data Scientist - Data Science & AI

Apr 2024 – Present · 2 yrs 2 mos · Mumbai, Maharashtra, India

Associate - Data Science & AI

Sep 2022 – Apr 2024 · 1 yr 7 mos · Mumbai, Maharashtra, India

Led end-to-end deployment of a Cross-Sell Model using XGBoost technique in PySpark, targeting inactive subscribers to boost revenue by 6.8% and customer retention by
23%, handling a dataset of 40+ million subscribers with Agile methodology. Orchestrated end-to-end migration of campaign and scoring reports from SQL Server
to Azure cloud, integrating Tableau dashboards; replaced Excel reports, resulting in a 40% increase in data accessibility and a 25% boost in analysis speed.
Engineered and optimized an end-to-end recommendation system for 32 million
DTH clients on Azure, leveraging Azure Databricks and Machine Learning Studio,
achieving 6-8% revenue growth and 48% efficiency improvement through automated data processes and CI/CD pipeline orchestration.
Developed and deployed ML models & reports, reducing processing time by 25%
through optimization techniques and creating stored procedures.
Led the enhancement of the LLM project using LangChain and OpenAI model to
convert natural language into SQL queries, significantly improving data analysis processes and delivering actionable insights & Prepared ROI reports for executive and
business teams using MS Excel or Tableau, resulting in a 25% boost in operational
efficiency.
Led a team of 5 to design & develop automated models & Reports to AWS Redshift and Tableau, streamlining workflow and enhancing productivity.