Data Scientist
Summary
I graduated with my master's in computer science with a focus on Data Science/Machine Learning in February 2023. I currently work as a SWE at a startup in DC(impacted by layoff).
These are my skillsets: SKILLS
Programming: Python, SQL, Golang, C, C++, MATLAB
Machine Learning: Linear Models, KNN, SVM, Decision Tree, Random Forest, Neural Networks, K Means Clustering, XGBoost, Naive Bayes, Feature Selection, Resampling (Cross-validation, SMOTE), Reinforcement Learning
Developer Tools: Jupyter Notebook, Visual Studio Code, Google Colab, PyCharm, Git, Linux, Docker, Kafka, EC2 Instance, AWS, Amazon Lambda, Postgres, Redis, Postman
Certification: Azure AI 900, SQL, Quantitative Modelling (Coursera), Software Engineering (CodePath)
This is the tech stack/responsibilities that I worked on:
Initiated and managed the development and deployment of package manager items using the Go programming language, streamlining
the intake of telemetry data and its subsequent transfer to data fusion using GRPC for comprehensive analysis.
Dockerised services and deployed them on the EC2 instances ensuring continuous data display on the user interface.
Directed the design, development, and deployment of orchestrator services, enabling customers to create pilot missions for drones and
reducing approval response times by 80 seconds. Engineered API solutions across three microservices and designed a database for
storing mission requests.
Developed a Golang parser to facilitate diagnostic data analysis of raw telemetry data, leveraging Python libraries to identify latency
issues, achieving an average latency reduction of 0.5 seconds. Implemented Python scripts for data cleaning, extraction, and
visualization, enabling detailed analysis of telemetry data and securing a contract with a client, increasing company revenue by
$100,000.
Optimized system efficiency by 70% through the development of test scripts using Postman Collection, contributing to the
establishment of a robust data capacity service.
Expectations
To learn and contribute to the team with my skillsets while gaining knowledge along the way. I want to work as a Data Scientist/Machine Learning Engineer
Employment Preferences
Relocation destinations:
- Herndon, Virginia, United States
- United States
Expected Base Salary
**,000 USD
Academic Degree
Experience
Total Professional Experience
Startup Experience
Enterprise Experience
Skills
- Programming Skills
- Python
- SQL
- Golang
- C
- C++
- MATLAB
- Machine Learning
- Linear Models
- KNN
- SVM
- Decision Tree
- Random Forest
- Neural Networks
- K Means Clustering
- XGBoost
- Naive Bayes
- Feature Selection
- Resampling
- Cross-validation
- SMOTE
- Reinforcement Learning
- Developer Tools
- Jupyter Notebook
- Visual Studio Code
- GoogleColab
- PyCharm
- Git
- Linux
- Docker
- Kafka
- EC2 Instance
- AWS
- Amazon Lamda
- Postgres
- Redis
- Postman
- Certification
- Concluded Azure AI 900
- Quantitative Modelling Through Coursera
- Software Engineering Course Via CodePath
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