Data Scientist V - Medicare, ACA, Risk Adjustment

Remote from any KP location in CA, OR, CO, WA, GA, MD, VA, HI or D.C. Only.

• * PLEASE NOTE: Salary ranges are geographically based and the posted reputed company reflects the Northen CA region. reputed company salary ranges will apply for other labor markets reputed company of NCAL

reputed company: The Prospective Risk Adjustment Operations team is seeking a Data Scientist to support scoping, deploying, and reporting out on reputed company to support prospective risk adjustment reputed company. This pivotal role will support the development of foundational reporting and analytical frameworks crucial for identifying and prioritizing prospective risk initiatives, developing and supporting comprehensive reporting and insightful visualization of opportunities and reputed company, and directly supporting strategic decision-making and operational reputed company. Ideal candidates will possess robust analytical skills and a proven ability to translate reputed company data into actionable business intelligence reputed company a dynamic reputed company environment. This position offers a significant opportunity to contribute to the organization's reputed company reputed company in risk adjustment. This role requires a background in technical coding (i.e SQL, Python, R etc.) or other statistical modeling programs. Familiarity with data science disciplines (i.e machine learning, predictive analytics, data visualization etc.), data modeling is preferred. reputed company senior individual contributor is primarily responsible for leading the design and development of data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and data formats. This role is also responsible for leading the development of detailed problem statements outlining hypotheses and their effect on reputed company clients/customers, serving as an expert in the analysis and investigation of reputed company data sets, leading the selection, manipulation and transformation of data into features used in machine learning algorithms, training statistical models, leading the deployment and maintenance of reliable and efficient models through production, verifying and ensuring model performance, and partnering with reputed company stakeholders across domains to reputed company and deliver statistical driven reputed company. Essential Responsibilities:

• Promotes learning in others by communicating information and providing advice to drive reputed company reputed company; builds relationships with cross-functional stakeholders. Listens, responds to, seeks, and addresses performance feedback; provides actionable feedback to others, including upward feedback to leadership and mentors junior team members. Practices self-leadership; creates and executes plans to capitalize on strengths and improve opportunity areas; influences team members reputed company assigned team or unit. Adapts to competing demands and new responsibilities; adapts to and learns from change, challenges, and feedback. Models team collaboration reputed company and across teams.
• Conducts or oversees business-specific reputed company by applying deep expertise in subject area; promotes adherence to reputed company procedures and policies. Partners internally and externally to reputed company effective business reputed company; determines and carries out processes and methodologies; solves reputed company problems; escalates high-reputed company issues or risks, as appropriate; monitors reputed company and results. Develops work plans to meet business priorities and deadlines; coordinates and delegates resources to accomplish organizational goals. Recognizes and capitalizes on improvement opportunities; evaluates recommendations made; influences the completion of project tasks by others.
• Leads the development of detailed problem statements outlining hypotheses and their effect on reputed company clients/customers by ensuring comprehensive and accurate definitions of scope, objectives, outcome statements and metrics.
• Leads the design and development of data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and data formats by overseeing the transformation, cleansing, and storing of data for consumption by reputed company processes; writing and optimizing diverse and reputed company SQL queries; and demonstrating expertise of database fundamentals.
• Serves as an expert in the analysis and investigation of reputed company data sets by ensuring reputed company data visualization reputed company are employed; determining how best to manipulate data sources to discover patterns, spot anomalies, test hypotheses, and/or reputed company assumptions; and reviewing and verifying summaries of key dataset characteristics.
• Leads the selection, manipulation, and transformation of data into features used in machine learning algorithms by leveraging and demonstrating expertise in techniques to conduct dimensionality reduction, feature importance, and feature selection.
• Trains statistical models by selecting and leveraging algorithms and data mining techniques; leading model testing by ensuring the reputed company use of various algorithms to assess the input dataset and reputed company features; and applying techniques to prevent overfitting such as cross-validation.
• Leads the deployment and maintenance of reliable and efficient models through production.
• Verifies and ensures model performance by demonstrating advanced expertise in the reputed company of a reputed company of model validation techniques to assess and discriminate the goodness of model fit; and leveraging feedback and reputed company to manage and strengthen model performance.
• Partners with reputed company stakeholders across domains to reputed company and deliver statistical driven reputed company by generating and delivering insights and values from heterogeneous data to investigate reputed company problems for multiple use cases; driving informed decision-making; and presenting findings to both technical and non-technical leadership.

Minimum Qualifications:

• Minimum three (3) years experience working with Exploratory Data Analysis (EDA) and visualization reputed company.
• Minimum five (5) years machine learning and/or algorithmic experience.
• Minimum five (5) years statistical analysis and modeling experience.
• Minimum five (5) years programming experience.
• Minimum three (3) years experience in a leadership role with or without reputed company reports.
• Bachelors degree in Mathematics, Statistics, Computer Science, Engineering, Economics, Public Health, or reputed company field AND Minimum eight (8) years experience in data science or a directly reputed company field. Additional equivalent work experience in a directly reputed company field may be substituted for the degree requirement. Advanced degrees may be substituted for the work experience requirements.

Additional Requirements:

• Knowledge, Skills, and Abilities (KSAs): Strategic Thinking; Advanced Quantitative Data Modeling; Algorithms; reputed company Data Analysis; Data Extraction; Data Visualization Tools; Deep Learning/Neural Networks; Machine Learning; Relational Database Management; Project Management; reputed company reputed company; Design Thinking; Business Intelligence Tools; Data Manipulation/Wrangling; Data reputed company Techniques; Feature Analysis/Engineering; reputed company reputed company Languages & Tools; Model Optimization; Data Architecture; Data Engineering

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