Prabodh Wankhede

AI Researcher

Montreal, Quebec, Canada3 yrs 7 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in building machine learning models and pipelines.
Achieved high accuracy in anomaly detection for drug manufacturing.
Developed a retirement assessment tool using Streamlit.

Stackforce AI infers this person is a Machine Learning Engineer with a focus on Healthcare and Fintech applications.

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Skills

Core Skills

Machine LearningDeep LearningData Science

Other Skills

Algorithm DesignAlgorithmsAlteryxAnomaly DetectionArtificial Intelligence (AI)Beautiful SoupCC++Computer VisionData AnalysisData CollectionData StructuresData VisualizationGitHeroku

About

Graduate in machine learning from UdeM/Mila with experience in building machine learning models and pipelines for production systems. Developed projects in automatic speech recognition, NLP, computer vision and causal inference. Highly skilled in PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, Plotly and Streamlit. I am interested in applied machine learning/data science research but owing to my work experience and academic coursework, I have an appetite for solving real-world problems across different domains. An optimist by nature. Nothing by halves. Loves programming. VISA: Canada Open Work Permit

Experience

3 yrs 7 mos

Total Experience

3 yrs 7 mos

Average Tenure

3 yrs 7 mos

Current Experience

Squarepoint

2 roles

Quantitative Developer

Promoted

Feb 2025 – Present · 1 yr 4 mos · Montreal, Quebec, Canada

Desk Quant Analyst

Nov 2022 – Feb 2025 · 2 yrs 3 mos · Montreal, Quebec, Canada

Université de montréal

Technical Assistant

Sep 2021 – Apr 2022 · 7 mos · Montreal, Quebec, Canada

Wrote Python scripts to scrape data from existing web pages to create new databases.
Compared and provided feedback on content operations platform to facilitate import/export of program description pages.
Updated admission requirements by country for graduate and postdoctoral studies.

Biointelligence technologies inc.

ML Research Intern

Jun 2021 – Feb 2022 · 8 mos · Sherbrooke, Quebec, Canada

Implemented multivariate LSTM-FCN for anomaly detection in the drug manufacturing process.
Achieved an F1-score of 0.99 (anomaly) to reduce the production costs due to contamination in the bioreactors.
Reduced the error rate for out-of-distribution data by training the model with outlier exposure.
Reduced model size by 67%, inference time by 40% and dataset memory usage by 50% without accuracy loss.
Wrote a pipeline in PyTorch for automated stateful training with dynamic features.
Collaborated with a cross-functional team to deploy the model into production on low-resource hardware.

PyTorchLSTM-FCNAnomaly DetectionModel DeploymentMachine LearningDeep Learning

Hec montréal

Independent Contractor

Feb 2021 – May 2021 · 3 mos · Montreal, Quebec, Canada

Worked alongside one of the research officers of IRE, HEC Montréal to develop a web application with Streamlit to assess individual retirement preparedness by taking into account the future evolution of earnings, the returns on the various types of financial assets, and the prices of residential real estate.
Link: https://cpr.hec.ca/

StreamlitWeb Application DevelopmentData AnalysisData ScienceMachine Learning