Yeshwant Kumar 🇮🇳 — Data Scientist

1. Versatile Quantitative Researcher: Experienced in quantitative finance with a strong foundation in advanced technologies such as Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, and Lifelong Learning Management Systems. 2. Quantitative Modeling: Proficient in designing and implementing quantitative models for pricing, risk assessment, and portfolio optimization, leveraging mathematical and statistical techniques alongside Machine Learning approaches to refine investment strategies. 3. AI-Driven Insights: Adept at utilizing Machine Learning and Deep Learning algorithms to extract valuable insights from complex financial data, facilitating data-driven decision-making and enhancing portfolio performance. 4. Interdisciplinary Expertise: Seamlessly integrating expertise in Computer Vision and Natural Language Processing to analyze visual and textual financial data, contributing to comprehensive investment analyses in multi-modal data environments. 5. Continuous Innovation: Passionate about exploring cutting-edge techniques and technologies, constantly seeking opportunities to enhance traditional quantitative methods with AI advancements, resulting in innovative investment strategies. 6. Lifelong Learning Advocate: Skilled in developing and implementing Lifelong Learning Management Systems (LLMS) to promote ongoing skill development and knowledge retention within quantitative finance teams. 7. ML & DL Enthusiast: Enthusiastically applying Machine Learning and Deep Learning methodologies to financial data, optimizing trading algorithms, risk assessment models, and market sentiment analysis for superior investment outcomes. 8. Results-Driven Innovation: Committed to achieving tangible results through innovation, consistently aligning AI-driven strategies with market opportunities to deliver alpha and maximize portfolio performance. 9. Educational Background: Hold a Bachelors in Computer Science from GIET University, complementing a strong quantitative foundation with expertise in AI and technology, creating a unique skill set for modern quantitative finance. Skillset primarily achieved from Nanodegree Certifications of Trading, Machine Learning and Deep Learning from Udacity.

Stackforce AI infers this person is a Fintech expert specializing in AI-driven quantitative finance solutions.

Location: Bengaluru, Karnataka, India

Experience: 7 yrs 3 mos

Skills

Machine Learning
Deep Learning
Nlp

Career Highlights

Expert in Machine Learning and Deep Learning for finance.
Developed AI-driven solutions enhancing investment strategies.
Strong interdisciplinary expertise in quantitative finance.

Work Experience

Wells Fargo

Data Scientist 2/Quant-AVP(AI & Machine Learning) (3 yrs 6 mos)

Great Learning

Data Scientist (1 yr 6 mos)

gnani.ai

NLP Deep Learning Intern (2 mos)

Pianalytix

Deep Learning Engineer (3 mos)

Self.

Freelance Developer (7 yrs 3 mos)

Education

Phd at Indian Institute of Technology, Patna

Masters in Financial Engineering at WorldQuant University

Licentiate degree at Udacity

Bachelor's degree at GIET University Gunupur

12th at Sri Chaitanya College of Education

Yeshwant Kumar 🇮🇳

Data Scientist

Bengaluru, Karnataka, India7 yrs 3 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Expert in Machine Learning and Deep Learning for finance.
Developed AI-driven solutions enhancing investment strategies.
Strong interdisciplinary expertise in quantitative finance.

Stackforce AI infers this person is a Fintech expert specializing in AI-driven quantitative finance solutions.

Contact

yeshwant.kumar@mlp.com LinkedIn

Skills

Core Skills

Machine LearningDeep LearningNlp

Other Skills

APIsAlgorithm DevelopmentAlgorithmsAlpha GenerationAmazon Web Services (AWS)Analytic Problem SolvingAnalytical SkillsArtificial Intelligence (AI)Automated TradingBERTC (Programming Language)C++ChatbotsCloud ApplicationsColab

About

Experience

7 yrs 3 mos

Total Experience

4 yrs 4 mos

Average Tenure

3 yrs 6 mos

Current Experience

Wells fargo

Data Scientist 2/Quant-AVP(AI & Machine Learning)

Dec 2022 – Present · 3 yrs 6 mos · India · On-site

Currency Autoconversion: Developed ML and DL models predicting destination currency for international transactions, minimizing conversion errors.
Document Similarity Analyzer: Built a system reducing turnaround time from hours to minutes by enabling quick navigation through relevant documents for the operations team in Wells Fargo.
Cash Liquidity Forecasting: Designed a Intraday Time Series forecasting model predicting bank liquidity using Time series models, traditional ML models, Neural Network and LSTM models.
Employee Attrition Analysis: Analyzed drivers of attrition, providing insights that reduced monthly attrition rates.
Support Ticket Categorization using LLMs: Built NLP models and tuned Llama and Mistral7B models using Langchain & Huggingface to categorize the support tickets, adding tags to tickets and obtaining response for the end customers.
Function Approximations using Deep Neural Networks over the traditional projection, gaussian and Adaptive sparse grid methods.
Using Neural Networks for optimizing Hamilton Jacobi-Bellman(HJB) Equation for optimizing decision making under uncertainty to solve macro-finance models with aggregate shocks.
Worked on Projects in core machine learning, NLP.
Worked on use cases related to fraud detection and text analysis
Acquired business knowledge related to several projects in banking industry
Understanding Monetary policies and financial markets
Tech Stack-> Python, Pyspark, ML Algorithms, DL Algorithms, Statistics, SQL, PyTorch, TensorFlow, BERT, APIs, NLP, GCP, MLFLow, MLops, Pyspark Machine Learning, Deep learning, Statistical Testing, A/B testing, and Model Monitoring, BERT, Transformers, Probability & Statistics, Hypothesis Testing, Partial Differential Equations(PDE's), Linear Algebra, Regression in depth, Trade Universe, Risk assessment, Signal generations, Portfolio Construction and Optimization, Basics of C++, Lime, NLP, Pyspark, H2O and Polars

PythonPysparkML AlgorithmsDL AlgorithmsStatisticsSQL+10

Great learning

Data Scientist

Jun 2021 – Dec 2022 · 1 yr 6 mos · Remote

Worked on Projects in Computer Vision and Neural Networks in collaboration with international universities which helped in increasing the company’s revenue by 40%.
Implemented several Machine Learning and Deep Learning models and deployed them using Gradio and Streamlit to include them in the academic curriculum for the international students of Great Learning.
Employed Data Analytics and Market Intelligence to identify the gaps in learning and increase the learning experience – increase in EPF.
Enhanced the content by doing Market Research to include use cases to keep the learners aware of the latest developments.
Interacted with learners from 10+ countries to clarify their doubts and help them grasp the topic better with relevant examples.

Gnani.ai

2 roles

NLP Deep Learning Intern

Apr 2021 – Jun 2021 · 2 mos · Bangalore Urban, Karnataka, India

Developed an AI Voice bot for credit and EMI services using python and RASA framework.
Developed an AI Voice-bot for EMI and Credit Card Services using Python and Rasa Framework.
Prepared Training data by creating NLU's and Stories for training the model.
Designed custom action files for validating several actions and functionalities like call-later and date validations.
Have done call integration and Call Orchestrator for enabling call services.
Trained the model on Server Machine and integrated it with Postman to test calls and used MongoDB to store and retrieve the call details.
Took several test calls to look after the call flow and made the necessary changes.
Designed templates for utterances given by the bot in English and Hindi languages.
Worked on trimming the audio in the voice calls to remove the trailing silence in the calls.

NLP Deep Learning Intern

Apr 2021 – Jun 2021 · 2 mos · Bangalore Urban, Karnataka, India

I have been working as an NLP Deep Learning intern to develop AI Voicebots to automate credit and EMI services in the financial industry.

Pianalytix

Deep Learning Engineer

Dec 2020 – Mar 2021 · 3 mos · Bangalore

Developed a Deep Learning model to count the number of screw outlets from the production of a company.
Gathered Data from a video source recorded during the production of screws and extracted each frame from the video and then used those images for training the model.
Used LabelImg to label the screws in the images for the custom input for YOLO and SSD architecture.

Self.

Freelance Developer

Mar 2019 – Present · 7 yrs 3 mos · India · Remote

Worked on Machine learning and Deep Learning projects
Understand thesis and writing white papers on Machine Learning, Deep Learning, Computer Vision and NLP
Building alpha research analogies using Machine learning, equity and crypto data