Recruiter LogIn

Don't have an account? Register now

Forgot Password?

Recruiter Registration

Custom

Select Your Default Landing Page

Photo

SHRUTHIPRIYA ** ******* Data Scientist

$720 / day

Summary

Deadline-oriented Data Scientist / AI Engineer with 6 years of experience in developing and implementing data-driven solutions. Possesses a strong background in Python, Large Language Models (LLM), statistics, SQL, Machine Learning, Artificial Intelligence, Cloud, and Software Engineering. Known for excellent communication and interpersonal skills, capable of working independently and as part of a team.

SKills

3D-CNNARIMAAutoMLAWS (DynamoDBAzure (ContainersAzure filesBart-large-CNNBERTBlob StorageCassandraClusteringCNNConfluenceContinuous Integration/Continuous Deployment Practices (CI/CD).Cosmos DBD3.jsData Lake)Decision TreesDecisionTreesDjangoDockerEC2Fast-APIFlaskGITGPTGPT-3Gradient BoostingHTMLHugging Face TransformersJava (Basic)JavaScript (Basic)JiraK-meansKubernetesLambdaLemmatizationLightGBMLinear RegressionLinearRegressionLinuxLLama2Logistic RegressionLSTMMachine Learning StudioMatplotlibMicrosoft Power BIMISTRALMongoDBMySQLNamed Entity RecognitionNLTKNoSQLNumPyOPEN AI (API)PandasPCAPegasusPlotlyPostgreSQLPROPHETPython (Advanced)PyTorchRandom ForestS3)SageMakerSARIMAScikit-LearnseabornSentiment AnalysisspaCySQLSQL (Intermediate)StemmingSVMTableauTensorFlowTokenizationTopic ModelingWekaWhisperXGBoost
AI ConsultantAI Software DeveloperData ScientistMachine Learning Engineer

Education

2016 Bachelor of Engineering at Visvesvaraya Technological University

Experience

Jan 2024 - March 2024 Data Scientist at SHAVIK AI

– Developed a 3D-CNN model for voice-based authentication achieving 99% accuracy for business and executive-level applications, with voice data stored in a Postgres DB for
retraining, using FastAPI.
– Created a package/library for gender-based classification using Keras achieving 96% accuracy for call center data analysis.
– Developed a RAG-based application using AWS cloud services and OpenAI models akin to AWS Bedrock (MVP).
– Implemented auto-generation of graphs using GPT-3 and Plotly.

Aug 2023 - Dec 2023 Artificial Intelligence Engineer at CONTACTPOINT 360

– Developed the Whisper model to transcribe customer audio into transcripts, processed using LLama2 (with and without PII data), and summarized conversations for business
reporting. Saved outputs in an S3 bucket for a call center client to gain insights into customer interactions.
– Designing and implementing an information retrieval and classification system for sentiment analysis using Spacy and NLTK.
– Utilised BERT for categorising calls to enhance precision and efficiency in call classification tasks.
– Integrated a customer support chatbot with the AWS Bedrock project, enabling the development and deployment of a scalable, secure, and cost-effective chatbot solution to
improve customer support services.

Nov 2023 - Jan 2024 Data Scientist at JSN

– Enhanced job search functionalities, personalised job recommendations, and overall user satisfaction.
– Developed the Pegasus model to summarise resume content, extracting name, phone number, and email using Spacy and NLTK.
– Integrated with job databases (Firebase), user-provided data, and implemented continuous learning mechanisms.

Nov 2020 - Oct 2022 AI/ML Engineer at SAMSUNG R&D

– Advanced skills in leveraging state-of-the-art technologies to develop innovative solutions across various domains.
– Applied Django, HTML, CSS, and deep learning models like RNN, LSTM, CNN to deploy a user-friendly walking pattern verification system, improving mobile accessibility and
scalability via SageMaker.
– Developed and maintained a Python application for sleep deprivation analysis, integrating Flask, Firebase, and machine learning algorithms (LR & RF) to deliver precise sleep
recommendations for organisation.
– Led a team of interns in creating an automated GUI testing tool using the Appium framework and Python for web apps with Flask.
– Engineered KLOC, a code analysis tool integrating NLP techniques (BERT) and MSSQL within a Django framework. The web application (HTML, JavaScript) enhances code comprehension
and decision-making capabilities, aiding in identifying issues and improvements, supported by enhanced reports using Power BI.
– Demonstrated proficiency in technical documentation and a commitment to driving data-driven insights, highlighting the ability to deliver impactful solutions in diverse
technical environments.

Nov 2019 - May 2020 Jr Data Scientist at ARTELUS

– Contributed to a comprehensive project targeting the early identification of Diabetic Retinopathy by extracting image features using Python in a UNIX environment.
– Integration of Azure AutoML with advanced machine learning techniques such as K-MEANS and SVM enhanced the accuracy and efficiency of the detection system, ultimately aiding in
the prevention of blindness.
– Spearheaded the development of a finished product prediction tool, incorporating Flask, HTML, JavaScript, and Bootstrap, with RNN and DL models (LSTM+CNN) in Python to forecast
finished products using historical data. The seamless integration of MongoDB further optimized data management and storage.
– In the context of Covid-19, utilized Python and CNN techniques to analyze chest X-ray images, contributing to the early detection and prevention of pneumonia.

July 2017 - Nov 2019 Python Engineer at QUALITEST

– By integrating Microsoft SQL Server into the ‘Daily and Weekly Internet Usage Analysis’ system, we enhanced the storage, retrieval, and analysis of internet usage data.
– Leveraged data visualization and machine learning techniques(Linear Regression) to analyze daily and weekly internet usage patterns and developed Python code to generate Call
Data Records (CDRs) and performed data visualization to extract insights for end users.