• Pre-processing - Demonstrate the skills and experience to collect, clean, and prepare data sets for input into a computational model using Python • Strong candidates will explain various methods you have applied using common pre-processing functions such as stop word removal, stemming, lemmatization, and tokenization • Feature Engineering and Attribute Evaluation - Candidate must demonstrate experience with NLP feature engineering methods such as TF-IDF, word2vec, GloVe, and FastText identifying the key determinants for modeling that exist in the business process and within existing data sets as well as selecting evaluation protocols (model techniques) • Modeling - Candidates will have practiced skills and experience selecting classification modeling techniques to fit the business problem. Examples will include techniques such as machine learning (ML) supervised and unsupervised learning, regression, neural networks and deep learning, natural language processing, etc. • Validation - Strong candidates will describe their experience with investigating, reporting, and justifying model results • Visualization- Experience in presenting the results of their modeling activities, depicting the insights realized, and explaining the relevance of their results to the organization’s business challenges

• Advance Root’s performance marketing capabilities through improvements in bidding systems, automation, and applied machine learning • Lead and develop a multidisciplinary team responsible for the deployment, optimization, and performance of a nine-figure annual marketing budget • Drive fast, disciplined experimentation across channels and partners • Develop strategic relationships with marketing and technology partners • Align priorities across Marketing, Analytics, Engineering, and Product

• Serve as the primary finance lead for assigned markets/focus areas • Own end‑to‑end financial support for IDN and PCP risk negotiations • Lead complex scenario analysis and large‑scale model adjustments • Translate enterprise models into market‑specific financial narratives • Partner with market presidents, contracting, and network strategy leaders • Set analytic priorities and manage multi‑deal demand • Provide direction, review, and coaching to support analysts and associates • Represent finance in market‑level strategy discussions and escalations

• Leveraging advanced analytical techniques and machine learning models to derive actionable insights from complex data sets. • Designing and implementing advanced data models and algorithms to solve complex business problems and drive strategic insights. • Conducting in-depth analyses of large and diverse data sets to uncover patterns, trends, and correlations that inform decision-making. • Collaborating with cross-functional teams to understand business needs and translate them into analytical solutions. • Developing and deploying machine learning models to enhance predictive capabilities and optimize business processes. • Providing thought leadership on data science best practices and emerging technologies to drive innovation and continuous improvement.