Senior engineering role at a fast-growing start-up in the payment orchestration space that handles millions of payments across the world. Worked in multiple cross-functional teams, and was responsible for system design, payment processor integrations, customer profile persistance, and API design. Responsible for owning technical initiatives from initial concept through to deployment in a live production environment.Tech stack:- FastAPI- Kubernetes- AWS- PostgreSQL- Redis

Technical team lead and product development role for a Personalized Healthcare and Genetics product for a greenfield team.Responsibilities include project management, end-user engagement, architecture design, software engineering, code review and mentorship. Primary decision maker for high-impact technical decisions.Tech stack:- Python (Django, PyData stack)- Cloud (Microsoft Azure -- Blobstore, Serverless, Docker, Kubernetes, etc.)- DevOps CI/CD (git, Bitbucket, Pipelines, etc.)

Responsibilities----------------- Handling and execution of "potential client" proof-of-concept projects- Machine learning workflow design and automation- Machine learning model design and iteration- Building infrastructure on cloud platforms- Warehousing and processing of large datasetsTechnical Skillset:----------------------------- Python (PyData stack + ML frameworks + NLP frameworks + Parallel processing frameworks )- Spark (via Databricks + standalone)- Cloud infrastructure (AWS + Azure stacks)- DevOps (Build automation, CI, etc)- Data visualization

Three month Data Scientist internship. Responsibilities included extensive data auditing, exploratory data analysis (EDA) as well as visualization of large datasets and accompanying analysis. Additional projects involved implementing templates for production-ready ML workflows and assisting in the implementation of cross-language support within a ML Python workflow and conducting a workshop to introduce clients to the new architecture.Notable skills developed:Production-ready PythonLarge dataset visualization (Datashader, Bokeh)Distributed data processing (Dask, Hive)

Six week Data Science internship program. Assigned to an internal team and tasked with producing work in Python across a variety of projects, requiring significant acquisition and development of Data Science skills. Additional responsibilities include attending planning meetings and contributing to team decisions.Projects:- Music generation using LSTM recurrent neural network.- Internal GPU feasability assessment and report. (related blog post: http://praelexis.com/2017/08/16/gpu-not-gpu/)- Exploratory data analysis and visualization of undisclosed dataset.Noteworthy skills include experience with modelling, training, evaluating and designing Neural Networks and other machine learning models using Keras, Lasagne and Scikit-learn frameworks (Python), as well as unit and integration test authoring and cloud computing experience across Amazon AWS, Microsoft Azure and FloydHub. Also includes additional development of data EDA and dataset visualization skillsets.