Lokendra Kumar Meena

Data Scientist

Bengaluru, Karnataka, India5 yrs experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in Natural Language Processing and AI technologies.
Proven track record in developing AI-based digital twins.
Strong background in data science and machine learning methodologies.

Stackforce AI infers this person is a Data Scientist specializing in AI and Machine Learning for manufacturing and technology sectors.

Contact

Skills

Core Skills

Natural Language Processing (nlp)Deep LearningArtificial Intelligence (ai)Machine LearningAlpha Generation

Other Skills

AirflowAlgorithm DevelopmentBERT (Language Model)C++CommunicationCorrelation AnalysisData AnalysisData CollectionData ModelingData ScienceData VisualizationDatasetsDebuggingDecision TreesElasticsearch

About

Passionate about leveraging cutting-edge technology to drive innovation and solve real-world challenges, particularly in Natural Language Processing and AI-based digital twin applications. 🎓 Academic Excellence: Graduated with a Bachelor of Technology in Civil Engineering with a Minor in Machine Learning & Applications from IIT-Kanpur. 💼 Experience: Data Scientist at Fractal Analytics (Present): Leveraged LLM - ChatGPT 3.5 to enhance automated insights generation and recommendations category growth via narrative building with retailer financial and demographic data sources. Leveraged my expertise in AI-based digital twin development to optimize manufacturing operations (Sinter). By integrating technologies like Self Adjusting Memory (SAM) KNN and AutoML, which significantly enhanced production throughput and reduced emissions. Previous Experience: Interned at Emplay, enhancing semantic search results for question-answering chatbots and boosting accuracy by 10-15%. 🛠️ Key Skills: Proficient in a wide array of tools and frameworks including Scikit-learn, Keras, TensorFlow, PyTorch, NLTK,

Experience

Fractal

Data Scientist II

Jun 2022 – Present · 3 yrs 9 mos · Bengaluru, Karnataka, India · Remote

◦ Leveraged LLM - ChatGPT 3.5 to enhance automated insights generation and recommendations, fostering category growth via narrative building with retailer financial and demographic data sources.
◦ Delivered an end-to-end Flask-based Python web app predicting consumer opinions, leveraging consumer response, formulation, and sensory data. Secured an F1 score ranging from 0.8 to 0.9 across various regions.
◦ Utilized Factor Analysis, PCA, and Bayesian Network to extract and comprehend

Deep LearningData CollectionDecision TreesAlgorithm DevelopmentCorrelation AnalysisPython+11

Eugenie.ai

Data Scientist

Jun 2022 – May 2023 · 11 mos · India

Model Development
◦ Researched and customized models inspired by Graphical Neural Networks, enhancing anomaly detection
and predictive maintenance precision in manufacturing operations.
◦ Transformed classical models into Incremental models, adapting to Concept Drift in real-time IIoT (Industrial
IoT) data, achieving a 25% increase in R2 score.
Prediction Pipeline
◦ Built an AI based digital twin for Tata metaliks (TML) and Vedanta industries, using 120 sensor
parameters that predicts optimal intermittent parameters, throughputs and emission.
◦ Incorporated Self Adjusting Memory(SAM) KNN and AutoML as backbone. Implemented automatic
feature selection for time series sensor data using RFE(Recursive Feature Elimination) and statistical tools.
Recommendation Pipeline
◦ Spearheaded the entire process of new user’s sensor data automation by streamlining data preprocessing, feature
engineering, end-to-end training, inference and recommendation pipeline.
◦ Utilized Genetic algorithms such as PSO, NSGA II, Hybrid PSO - NSGA II to drive process optimization.
◦ Significantly increased production of Sintering machine by 5 Ton/h and reduced emissions by 13% on average.

Deep LearningData CollectionDecision TreesObject-Oriented Programming (OOP)Algorithm DevelopmentCorrelation Analysis+24

Emplay inc.

Data Science Intern

Jul 2021 – Dec 2021 · 5 mos · Remote

Objective: To improve semantic search results used in Question-Answering Chatbot
◦ Obtained a better contextual understanding of the query by incorporating semantic search into the Natural
Language Processing (NLP) phase of the pipeline.
◦ Developed an End to End question answering pipeline from given content using Haystack and tested using Postman
◦ Improved Semantic search by crushing data into Title, Sub-title, Body & Description by assigning different weights

Deep LearningObject-Oriented Programming (OOP)Semantic SearchhaystackPythonDebugging+9

Topbrain technology

Machine Learning Engineer

Mar 2020 – Jun 2020 · 3 mos · India

Back testing various market strategies for automated intraday trading.
Learnt basics of finance, quant-based trading, market strategies, ratios, indicators and analyzers related to stock market.
Learnt backtrader, an open-source platform for back testing and trading, and its integration with other libraries.
Implemented multiple types of orders based on strategies and signals generated by OHLC data.

Object-Oriented Programming (OOP)PythonDebuggingData ModelingAlpha GenerationDatasets