Summary
Overview
Work History
Education
Core Competencies
Publications
Timeline
Generic

SNEHA PULLELA

Research Scientist
Ottawa,ON

Summary

Results-driven Data Scientist with over 4 years of experience in developing and deploying deep learning and machine learning models for computer vision, similarity detection, and image segmentation tasks. Proven track record of using experimentation and data-driven insights to reduce manual labor by 50%, streamline workflows, and deliver production-ready solutions. Skilled communicator adept at collaborating with stakeholders, mentoring co-op students, and iterating based on feedback. Passionate about continuous improvement and driving high-impact innovation.

Overview

7
7
years of professional experience
2023
2023
years of post-secondary education

Work History

Research Scientist

TechInsights
OTTAWA, Ontario
02.2022 - Current
  • Designed and deployed deep learning models (YOLO, UNet, HRNet) for image segmentation and object detection, achieving a 50% reduction in manual review time.
  • Led A/B testing initiatives to evaluate model performance and workflow optimizations, enabling data-backed deployment decisions and ensuring incremental impact measurement.
  • Applied causal inference principles (uplift modeling, stratified sampling) to isolate and measure the business impact of new ML solutions, directly influencing strategic decisions.
  • Developed and maintained Python APIs and Flask web applications to deliver scalable ML solutions to internal teams.
  • Collaborated with stakeholders to define experimentation goals, gather feedback, and iterate on solutions, ensuring alignment and business value.
  • Mentored junior team members on ML best practices, code quality, and experimentation design.

Research Scientist Co-op

TechInsights
OTTAWA, Ontario
01.2021 - 12.2021
  • Built tools for image clustering and search using ML techniques like Decision Trees, SVMs.
  • Developed internal search engine using regex, MongoDB, HTML, JavaScript.
  • Used HRNet for improved image segmentation in microscopy images.

Software Engineer

Capgemini
HYDERABAD, INDIA
06.2018 - 12.2019
  • Owned automation regression testing and maintained high-quality test plans.
  • Developed scalable and maintainable code, ensuring long-term stability of the software.
  • Implemented effective debugging strategies, resulting in fewer software defects and increased reliability.

Education

Master of Computer Science -

University of Ottawa
Ottawa, ON
01.2022

Core Competencies

Languages & Tools: Python, SQL, JavaScript, HTML/CSS, Git, Postman, AWS (EC2, Lambda, S3)
Libraries & Frameworks: TensorFlow, PyTorch, Scikit-learn, OpenCV, XGBoost, Flask, MongoDB, Pandas, NumPy, Seaborn
Techniques: A/B Testing, Experiment Design, Causal Inference (intro level), Image Segmentation, Object Detection, Feature Extraction
Soft Skills: Collaboration, Agile Communication, Mentorship, Cross-functional Teamwork, Stakeholder Engagement

Publications

Z. Yu et al., "A Data-Driven Approach for Automated Integrated Circuit Segmentation of Scan Electron Microscopy Images," 2022 IEEE International Conference on Image Processing (ICIP), Bordeaux, France, 2022, pp. 2851-2855, doi: 10.1109/ICIP46576.2022.9897544. 

Timeline

Research Scientist

TechInsights
02.2022 - Current

Research Scientist Co-op

TechInsights
01.2021 - 12.2021

Software Engineer

Capgemini
06.2018 - 12.2019

Master of Computer Science -

University of Ottawa

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