Develop ETL procedures connecting financial services to internal data stores (Salesforce).

Build Python applications to move data between systems, validate calculations, apply business logic.

Develop front-end (React) web application to ingest data from clients and teams with a FastAPI Backend (Python).

Write data pipelines in Python, Azure Data Factory, Azure Function Apps to manage data movement and scheduling.

Standardize processes to build and launch updates to applications through Azure DevOps and Azure Pipelines (CI/CD).

Maintain GitHub repository for active development and source control.

Manage and customize infrastructure in Azure for authentication, networking, data management, security, and billing.

Recommend, review, and scope new technology platforms for use internally.

Develop API data ingest programs to query healthcare databases and write to Snowflake.

Convert analytics and insights into presentable dashboards and workbooks in Tableau and PowerBI.

Generate financial data models to be consumed and transformed by the PowerBI data platform

Gather and interpret analytic requests and work with statistical analytic teams for development of medical economic dashboards in Tableau.

Visualize Tableau logs for access control and database refresh priority scheduling.

Manage Tableau Server, including maintenance scripts, user account management, and connectivity to data warehouses.

Assist with infrastructure in the Azure platform including connectivity, deployment of Function Apps, and data security and storage.

● Architect and design business intelligence solutions and processes to improve reporting frameworks and visualize findings and insights

● Create dashboards and visualizations (utilizing Microsoft BI and Einstein Analytics) for multi-functional organizations with an emphasis on metrics, efficiency, optimization, reporting, quality assurance, and error detection.

● Develop data warehousing solutions in the Snowflake data lake platform

● Create data marts to generate data driven insights

● Gather requirements and gaps from internal stakeholders to be implemented into solutions that accelerate productivity, reduce costs, and provide data driven insights to business and functional units.

● Provide cross-functional training on business intelligence tools

Helping to develop an open source analytics platform that harnesses the power of AI and NLP to accelerate, enhance accuracy and efficiency of contract review and analysis

• Machine Learning, Big Data, Distance Metrics, K Nearest Neighbors, Clustering, Decision Trees, Ensemble Methods, Dimensionality Reduction, Pipeline Building, Hyperparameter Tuning, Grid Search, and Scikit-Learn

• Deep Learning, Natural Language Processing, Neural Networks, Convolutional Neural Networks, Ngrams, POS Tagging, Text Vectorization, Context-Free Grammars, Neural Language Toolkit, Regular Expressions, Word2Vec, and Text Classification, Tableau, Hive, SparkData Engineering, Data Cleaning, Pandas, NumPy, Matlotlib/Seaborn for Data Visualization, Git/Github, Data structures, Relational Databases, SQL, Object-Oriented Programming, NoSQL databases, MongoDB, JSON, HTML/XML, Accessing Data Through APIs and CSS Web Scraping

• Probability Sampling, AB Testing, Combinatorics, Probability Theory, Statistical Distributions, Bayes Theorem, Naive Bayes Classifier, Sampling Methods, Monte Carlo Simulation, Hypothesis Testing and AB Testing

• Statistical Modeling, Linear Algebra, Linear Regression and extensions, Polynomials, Interaction effects, Logistic regression, Optimization Cost Function, Gradient Descent, Maximum Likelihood Estimation, Time Series Modeling, Regularization and Model Validation

• Python for Data Science, Variables, Booleans and Conditionals, Lists, Dictionaries, Looping, and Functions