Nikunj Kumar Singhal

CEO

Mumbai, Maharashtra, India11 yrs 6 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Led development of India's first AI-ML mutual fund.
Expert in quantitative investment strategies and data science.
Proficient in Python, SQL, and advanced analytics tools.

Stackforce AI infers this person is a Fintech expert specializing in quantitative investment strategies and data analytics.

Contact

Skills

Core Skills

Data SciencePortfolio ManagementQuantitative InvestingMachine LearningRecommendation SystemsData AnalyticsNlpText Analytics

Other Skills

AI-MLAnalysisAutoCADBloombergBloomberg Data LicenseClustering AlgorithmsData MiningData ProfilingEquitiesEquity DerivativesFactor investmentHTMLMatlabMicrosoft ExcelMicrosoft Office

About

Leveraging my extensive experience in Data Science, I bring a wealth of knowledge in quantitative analysis and strategy development, particularly in the realm of asset management. My tenure at Tata Asset Management has honed my skills in portfolio management, where I executed innovative multi-factor investment models and spearheaded pioneering projects like the Tata Quant Fund. My technical acumen is further solidified by my proficiency in Python, SQL, VBA, and my adeptness with tools like Bloomberg and advanced Excel. I am passionate about leveraging quantitative research to create differentiated, robust investment strategies and am always eager to explore new ideas and manage large datasets with precision and attention to detail.

Experience

Tata mutual fund

2 roles

Chief Manager - Data Science - Quant

Promoted

Jul 2024 – Present · 1 yr 8 mos · Mumbai, Maharashtra, India

Leading development of innovative data-driven quant investment strategies

Data ScienceQuantitative AnalysisPortfolio Management

Senior Data Scientist

Sep 2018 – Jun 2024 · 5 yrs 9 mos · Mumbai, Maharashtra, India

Designed and developed machine learning driven Tata Quant Fund
1st mutual fund scheme in India to employ AI-ML in investment space
Active multi factor investment model that dynamically changes factor strategies based on prevailing market conditions

Machine LearningQuantitative InvestingAI-ML

Info edge india ltd

2 roles

Senior Data Scientist

Promoted

Apr 2017 – Aug 2018 · 1 yr 4 mos

Recommendation systems (naukri.com, jeevansathi.com), Random Forest, Machine Learning, Python, R

Recommendation SystemsRandom ForestMachine LearningPythonR

Data Scientist

May 2016 – Mar 2017 · 10 mos

Impetus

Analytics Engineer

Jul 2014 – May 2016 · 1 yr 10 mos · Bengaluru Area, India

Worked as an Analytics Engineer for Impetus. As part of my job profile, i have worked on
Supplier Recommendation : Implemented clustering algorithm(k-means) to find peer sets of corporate clients of American credit card company.
Developed recommendation system to suggest suppliers to client that it may be do business with.
I worked in a global team and collaborated on a day-to-day basis with my offshore colleagues based in New York.
Text Analytics & NLP: Performed sentiment analysis on restaurant reviews
Developed recommendation system for an online restaurant review website.
Network Analytics: Identifyied top influencers in the company though email network graphs
Applied Topic Modeling to identify hidden topics in discussions on exchanged emails.
Developed an R based ETL solution for data profiling, cleaning, standardization, de-duplication and mapping involving implementation of supervised and unsupervised machine learning algorithm.
Tools: R, RStudio, Platfora(Basic), Excel

Clustering AlgorithmsText AnalyticsNLPData ProfilingData Analytics

Hindustan aeronautics limited

Summer Intern

May 2012 – Jul 2012 · 2 mos · Koraput Area, India

Completed projects titled
1. "Study and Optimisation of Manufacturing Process of 1st stage Turbine rotor blade for TV-3 Turbo Shaft Engine" : Suggested a change in the process sheet to decrease the rejection rate in the manufacturing of the blade.
2. "Determination of stacking axis of 1st stage turbine blade" : Analysed the stress and moments acting on the different cross-sections of the blade to optimize the position of the stacking axis .