Verified Expert in Engineering
Data Scientist and Developer
In her more than eight years of experience, Jana has worked at both small and large companies and has been through many stages of growth. She has also collaborated with people across the tech industry, including executives, designers, product managers, engineers, business leaders, and marketers. Jana's job is to take loosely defined problems, design robust solutions, and find the quickest path to implementation while ensuring the solution is never a "black box" for the client.
Python, SQL, Amazon SageMaker, Apache Airflow, Jupyter Notebook, Pandas
The most amazing...
...initiative I've led was revamping the pricing algorithm at an online car retailer by introducing new ML techniques and automating model training and deployment.
Lead Data Scientist
- Designed, built, tested, and iterated on machine learning (ML) algorithms across the business. Used techniques such as regularization, ensembling, gradient boosting, cross-validation, and dimensionality reduction.
- Found and validated external and internal data sources to support models.
- Increased organizational trust by building data visualizations to explain “black box” models. These models are sufficiently complex that they are not straightforwardly interpretable to humans.
- Worked with business stakeholders to identify key areas of opportunity related to the accuracy and scalability of pricing algorithms to optimize for business metrics such as GPU, revenue, and sales volume.
- Collaborated with the data engineering team to establish requirements for and build the first ML model training and deployment system using Amazon Sagemaker for live inferences and Apache Airflow for batch inferences.
- Built out monitoring systems for production models to track input and output over time and catch degradations in quality.
- Ran technical screens for data science team candidates. Onboarded and mentored more than five new data scientists.
- Acted as the interim data science manager during a three-month gap in leadership.
Senior Data Scientist
- Supported a product suite that produced a continuous stream of data related to wireless network usage and performance from over 100,000 mobile devices.
- Built out algorithms for data anomaly detection, predictive modeling of customer satisfaction based on network performance, and data pipeline management.
- Collaborated cross-functionally to productionize these algorithms.
- Hired as the first full-time data scientist on the product suite. Helped expand the team by interviewing and training four new data scientists.
- Established the tool set, coding standards, and best practices for the team.
Data Analyst | Statistical Programmer
- Developed, optimized, and documented SAS programs for ETL and analysis of large Medicare and Medicaid claims datasets to support government healthcare research projects.
- Created and implemented risk models to identify healthcare providers who systematically over-utilize Medicare resources or have patients with poor health outcomes.
- Led SAS and SQL training classes for new programmers and managed interns.
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Python, SQL, SAS, R
Sisense, Tableau, Microsoft Excel, Amazon SageMaker, Apache Airflow, GitHub, Git, Bitbucket
Data Science, ETL, Testing
Jupyter Notebook, Oracle, AWS Lambda, Amazon Web Services (AWS), Docker, Amazon EC2, Zeppelin, Databricks
PostgreSQL, Databases, Redshift, Amazon S3 (AWS S3)
Regression, Data Analysis, Data Visualization, Statistical Analysis, Model Development, Web Scraping, Data Queries, Algorithms, Artificial Intelligence (AI), Data Reporting, Data Analytics, Big Data, Machine Learning, Statistics, Gradient Boosted Trees, Random Forests, Supervised Learning, Unsupervised Learning, Modeling, Forecasting, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Research, Healthcare IT
Bachelor's Degree in Mathematics and Physics
Georgetown University - Washington, DC, United States
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