Reetayan Das

I am passionate about finding meaningful insight from the data. A storytelling is an interesting way I follow to make the data reusable for future aspects. I worked on statistics, predictive analytics and data pipelining. I perform and share experiments with other data scientist about trend analysis for technical aspects on development of AI through collaboration on social platforms.

I have worked on Automotive industry, financial services, engineering industry as a Data Scientist and Data analyst. In Every cases I tried to put my contribution so the end product will have an positive effect.

As a passionate Data Scientist, I have the experience needed to help the company grow. I am dedicated to continuously learning and enhancing my skills. I admire Company’s dedication to data-informed product building, and I would be thrilled to join the team. I have attached my resume, which further outlines my education and experiences.

Senior Data Scientist

Hexagon A&P Canada, Ottawa -2023/Jan- Present

• Automated pipeline for Image positioning and Object Detection Control systems and created dashboards which monitors scalability and feedback for data driven deployment.

Tools: Python, spark, data bricks, Scala

• Statistics Implemented for Stereo and Surround view Cameras for Different Categories for Object Detection with predictive analytics. Tools: Python, PostgreSQL
• Showcasing statistics Report in a dashboard of Confluence with automation and attached in an end-to-end solution in aws. Tools: Python, AWS, NoSQL

 

Data Analyst

Zions BanCorporation (Utah) -Remote, 2021/June – 2022/Dec

• Analyzed Customer data and automated customer invoice software based on reporting components and predictive analytics for a better decision making for stakeholders.

Tools: SQL, R, ADO

• Built Data pipelineto make the Agile Environment faster than 2 sprints with a 95% accuracy.
• Provided best profitable solution for customer accountfor the most reliable customers in next1 year in the finance market. Tools: Python, R, Tableau

Data Scientist

SENSEZ9, Seattle, 2020 Aug - 2021 June

• Implemented algorithms for voice cloning application with RNN on real-time audio data and deployed on production environment with 95% accuracy in small amount of time. 

Tools used: Python, OpenCV,TensorFlow, jupyter notebook

• Visualized several audio frequencies with their descriptive statistics and automated them with embedded Analytics with power Bi and Cross functional analysis.
• Built Data pipeline to automate the ml model 3 times faster and monitoring performance.

Data Analyst

AMDOCS, India, 2014 - 2017

• Performed extensive Data analysis of historical data and maintenance of it’s design structure.
• Provided onsitetraining to clientsfor new products& facilitated the integration in their system.
• Executed database solutions with PostgreSQL, python.
• Deployed data pipelines in production environments sourcecode repositories and generated qualitycontrol reports.
• Performed Devops operations for Billing product of Amdocs.

MS in ComputerScience in Data Science

Clemson University, Clemson SC 29631,United States, 2018 - 2020

Graduate Research Assistant

CLEMSON UNIVERSITY, Clemson SC 29631, UnitedStates, 2018 – 2019

• Analysis of Spotify Data on track features and user Behaviors and created a recommendation system statistical programming and regression analysis with kpi metrics.
• Built-up innovative user profiling on Bayesian clustering and identified the user Similarity-based on the correlation values on musical taste. Tested the GUIwith TestComplete
• Tested with SVM classifier gained18% accuracy than baseline. Tools: Python, R,Tableau

Voluntary researcher

CLEMSON UNIVERSITY, Clemson SC 29631, UnitedStates, 2019 - 2020

• Voluntary startup researcher of Covid-19 testingof students at Clemson University.

Built a DecisionTree classifier (supervised) to predict the oncoming Severityof mental conditions based on patient’s risk factor and medicalhistory. Tools used: Python, MySQL, R.

Heart diseasePrediction 12/2018- 06/2019 Early warning system of heart disease prediction using Cleveland clinic Dataset with 94% accuracy of predictive model in a regulatory environment.

Tools: Python 

• Amazon productanalysis 08/2019- 12/2019 Extraction of facets of amazon product reviews (unsupervised) to create a richer modelof product satisfaction using bag of words strategy. Product appeal score was0.92543.

Tools: Python, SQL, aws

• Employee attrition analysis 06/2020-09/2020 

Prediction of Employee attrition in an organization based on their mental health with 93% accuracy.

• Imageclassifications on road signs 12/2019-05/2020 Developed classification algorithm, based on the neuralnetworks for recognizing road signs on adverse conditions with 95% accuracy and implemented it aws.

• CrimeRate Prediction for Boston City 12/2019-05/2020 Prediction of occurrence of crime in particular counties of Boston city and predicted the most Crime infected area and type of crime in future timeframe with the help Decision tree classifier, SVM and Xgboost with an accuracy rate of 91%.

• Object Detection on GTA-V

Object detection with Tensorflow model (91.6% accuracy)when tested on electronic game GTA-V. Implemented a self-driving model with 96%accuracy.

Tools: Python, Pytorch,Tensorflow, AlexNet, scikit-learn