Reetayan Das

Data Scientist Experienced working with real-world large data sets and applying interpretations to complex business concerns. Proficient in distribution, forecasting, feature engineering and anomaly detection in fast paced environment. Bringing 6 years of relevant experience in quantitative field strengthening company operations.

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.

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 pipeline to make the Agile Environment faster than 2 sprints with a 95% accuracy.
• Provided best profitable solution for customer accounts for 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.

Graduate Research Assistant And MS in Computer Science

CLEMSON UNIVERSITY, Clemson SC 29631, United States, 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, United States, 2019 - 2020

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

Built a Decision Tree classifier (supervised) to predict the oncoming Severity of mental conditions based on patient’s risk factor and medical history. Tools used: Python, MySQL, R,