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Candidate Details

Name :

Keshav K L
Qualification :
Data Science Manager
Industry :
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Data Science Manager

About our Client

Dynamic leader in HR Data Analytics with over 11 years of experience in implementing Artificial Intelligence and machine Learning models and using data science techniques in R and Python to drive technological innovation in transformative HR solutions.

Results-driven Data Science Leader with a proven track record of implementing AI/ML techniques at an enterprise level. I am excited about the opportunity to contribute to your esteemed organisation and am confident in my ability to help achieve your goals. Let's connect to discuss how my skills and experience align with your needs.



Artificial Intelligence: Experienced in Generative AI algorithms with the development of RAG models for chatbots using Azure OpenAI, data embedding using Ada Models, Search and Retrieval using Vector databases like Weviate, Azure Cognitive Search and Redis.

Statistical Analysis/ Machine Learning: Proficient in Regression models, Hypothesis Testing, PCA, and supervised Machine Learning algorithms including RandomForest, and Gradient Descent, with hands-on experience in building and deploying ML models.

Programming Languages: In-depth knowledge of R and Python with a successful track record in building end-to-end applications using R-Shiny and Flask architectures. Hands-on Experience in handling queries in SQL.

Certification or Training: Certified in Six Sigma Green Belt for process Optimization using Statistical Analysis.

Leadership: Exceptional leadership skills demonstrated through end-to-end development and delivery of analytics tools for Human Resources.

Professional Experience

Data Science Manager

Flight Risk: Spearheaded the development of Flight Risk, for employees, helping in proactive retention of high-risk employees with the reduction in attrition and more than US$ 2Million in cost savings.

Generative AI: Pioneered the integration of Generative AI in HR through Azure OpenAI, building a RAG model for HR to answer employee queries. The model was trained on HR policy and records data to answer user queries in an efficient manner, improving response times by 30%.

Succession Planning: Developed an Intelligent Succession Recommendation model using predictive analytics and NLP to match successors to roles based on skills, performance, and historical data, successfully improving internal jobs filled by succession from 15% to more than 35% in key positions.

Architecture Design: Designed and developed architecture for deploying our models and showcasing them through dashboards in R and Shiny using a Virtual machine and R Studio-Connect.

Mentorship: Mentored several junior team members, contributing to their professional development and growth within the organisation. Currently mentoring cross-functional members for internal movements.

Team: Established a pioneering data science team that enhanced decision-making in HR functions. Expanded the team from three analysts to ten data scientists and software developers, demonstrating innovation and strategic foresight.

Predictive Analytics Analyst

Statistical Analysis: Established a Statistical Analytics framework for analyzing effectiveness of talent development programs and retention programs with Hypothesis Tests and regression analysis.

Text Analytics: Worked on several NLP projects providing insights from text sourced from surveys and other sources. Worked on LDA and TF-IDF analysis to get relevance of words from years of survey data.

Forecasting: Demonstrated my ability to build forecasting models for Workforce Planning, Turnover Forecasting and Requisition Forecasting by utilizing internal data and external economic data like inflation, FED rate, Unemployment, GDP Growth etc..

Senior Analyst - Data Science

• Integrated statistical tests and inferential algorithms into the Salesforce ecosystem via the app interface using the R Shiny ecosystem, enhancing data-driven decision-making.


• Developed comprehensive risk rating models for suppliers based on a range of operational and financial metrics, conducting real-time risk reviews and alert triggering based on 150+ parameters for suppliers, significantly enhancing risk mitigation strategies.

Research Analyst

• Developed financial valuation models for Ultra High Net-Worth individuals based on 50+ parameters, aiding in strategic investment decisions. Estimated engagement risks through due diligence, enhancing client confidence and investment safety.


Master’s Degree of Business Administration in Information Systems Management

Relevant Coursework: Systems Planning and Design and Enterprise Architecture Design

Thesis/Dissertation: Design of Vulnerability Assessment protocols for University Servers

Bachelor’s Degree of Engineering in Computer Science Engineering

Relevant Coursework: Software Engineering, Programming Languages, Data Structures

Thesis/Dissertation: Optical Character Recognition (OCR) using Java libraries.


Running/Sports: I am passionate about running and dedicating time to improving my stamina for long-distance running. Targeting to complete a half-marathon by Dec 2024. I am a huge football fan (Soccer) and love to support my favourite team, Chelsea FC.

Generative AI and Data Science: I have a keen interest in AI in general and Generative AI in particular. I believe this is the next evolution of data science and very useful for organisations to embrace it.

Animal Support/Sustainability: I am actively involved in helping stray dogs to get proper care. On weekends, I go out and provide food and water to stray dogs.


Technical Skills

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