Johnathon Kyle Armstrong

I am a collaborative and results-focused Data Science professional with an extensive background in analytics and a doctoral degree in Mathematics. Utilizing this background I take my expert knowledge in mathematics, statistics and data analysis and apply it to solving complex business problems and challenges. I have experience working as a Data Scientist, Research Scientist, and senior statistical lead on projects. In addition to these skills, I utilize excellent communication and interpersonal skills to build rapport with stakeholders, and ensure a positive customer experience. In addition, I use my adaptability and decisiveness to produce results in fast-paced and deadline driven environments. Finally, I maintain an expert level knowledge of the latest technologies and approaches. 

𝑻𝒆𝒄𝒉𝒏𝒊𝒄𝒂𝒍 𝑺𝒌𝒊𝒍𝒍𝒔 
𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬: R, Python, SQL, SAS
𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭: TeraData, Spark, Impala, PostGres, Snowflake 
𝐂𝐥𝐨𝐮𝐝 𝐃𝐚𝐭𝐚 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭: Google Cloud, Google Big Query, Amazon Web Services, Cloudera Data Science Workbench 
𝐃𝐚𝐭𝐚 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Tableau
𝐕𝐞𝐫𝐬𝐢𝐨𝐧 𝐂𝐨𝐧𝐭𝐫𝐨𝐥: Git 
𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐚𝐥: Data Analytics, Visualization, Machine Learning, Project Management, Statistical Modeling, Predictive Modeling, Team Development, Leadership, Optimization, AI

Independence Blue Cross
Senior Research Scientist, Advanced Analytics & Data Science
May 2018 - Jun 2022 · Philadelphia, PA

𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬
• Actively research and utilize the latest developments in machine learning and artificial intelligence to work on projects involving both structured and unstructured data.
• Lead data scientist and machine learning engineer on projects, working with stakeholders to gather requirements and make key decisions on methodology, process, and code.
• Develop and implement machine learning pipelines to solve complex business challenges.
• Evaluated medical management programs to determine their clinical and financial outcomes and provided recommendations to Executive Management.
• Provide mentorship and promote best practices related to code standards and optimization.
• Collaborate with business partners to develop statements of work and partnerships with research organizations.

𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬
• Managed ETL processes and SQL using R, Python, TeraData, HIVE, and Impala for data wrangling to support 40+ machine learning models, reducing model creation time from months to weeks.
• Developed Likelihood of Impact predictive model to identify members likely to have cost savings with Case Management, using nearest neighbor and random forest classifiers. 
• Built an Adverse Pregnancy Outcomes Predictive Model using OMOP CDM to identify pregnancies and multiclass classifier to predict normal pregnancies, various adverse events, or deaths.
• Created Estimation of Cost Estimates for Commercial Population Spark Random Forest regression model, providing monthly estimates on total medical costs to inform cost-saving initiatives.