Data Scientist
9/2021 - Present
- Led and directed all data science projects, providing comprehensive leadership and guidance to ensure successful project delivery.
- Utilized Agile methodologies with Jira and Kanban methodologies with Trello to streamline project management processes.
- Facilitated effective communication and collaboration among team members using platforms such as Slack, ensuring seamless coordination and timely project completion.
- Leveraged MongoDB with geoJSON data structures for efficient storage and retrieval of geolocation data, enabling visualization of spatial patterns and trends for informed decision-making.
- Applied common data science frameworks like Keras Tensorflow and PyTorch to develop Convolutional Neural Networks (CNNs) for anomaly detection in clinical imaging data, improving diagnoses and subject care.
- Demonstrated proficiency in Large Language Models (LLMs), particularly in sentiment analysis and natural language processing (NLP) tasks using survey data collected from millions of data points.
- Conducted ETL and analysis of client data using a typical data science stack including Pandas, Numpy, Sci-Kit Learn, Matplotlib, and SciPy, translating findings into actionable strategies fulfilling business objectives.
- Implemented customer segmentation and analysis using machine learning techniques such as K-means, PCA, and UMAP to identify key segments and uncover trends for strategic decision-making.
- Developed interactive dashboards with Plotly Dash and Tableau to visually showcase data trends, enabling stakeholders to make data-driven decisions and achieve organizational success.
- Aligned client objectives with KPIs and metrics tailored to personalized self-care, health, and beauty trends, ensuring precise strategic insights for informed decision-making.
Data Scientist
9/2021 - 9/2022
- Collaborated cross-functionally throughout the end-to-end data science lifecycle, including data wrangling, exploratory analysis, hypothesis testing, modeling, rapid prototyping, validation/testing, and deployment.
- Applied advanced analytical techniques such as predictive modeling, machine learning, and optimization.
- Utilized diverse structured and unstructured data to derive meaningful insights for modeling.
- Effectively communicated complex analytical work to technical and non-technical stakeholders.
- Maintained knowledge of emerging data science techniques, technologies, and ML/AI applications.
- Launched a decision-making analytic platform as Product Owner, leveraging Agile and Scrum.
- Partnered with business leaders, delivering high-impact data products aligned with company strategy and customer experience.
Postdoctoral Researcher
9/2020 - 9/2021
- Created, designed, and developed analytical pipelines for big data, e.g., next-generation Sequencing (NGS Data).
- Performed extraction of data from relevant databases using Python in UNIX and Cloud/High-Performance Computing (HPC) environments (data management).
- Lead several lab projects; Collaborated and reviewed protocols of research methodology; Assisted in planning and documentation of group projects and grants.
Graduate Researcher & Teaching Assistant
1/2017 - 9/2020
- Dissertation focus: Annotation of A. sativa genome (Illumina and PacBio) and identification of transposable elements.
- Designed, developed, and deployed a real-time analytical pipeline utilizing data extracted from large bioinformatics databases (NCBI, Genbank, EMBL); Developed in an academic Agile environment throughout the development cycle.
- Instructed Masters and Undergrad courses and performed research (BINF 3201, Genomic Methods for Bioinformatics); Introduced students to various technologies and methodologies utilized in bioinformatics and biotechnology industries.
