Description: Job Summary:

The Content, Search and Personalization (CSP) team is looking for a Sr. Staff Data Scientist for Recommender Systems and Personalization. You will work with team members and cross functional partners and leverage machine learning, deep learning, NLP, graph algorithms and Big Data technologies (Spark, NoSQL databases, Distributed Real-time Systems), cloud platforms such as Azure ML, and general purpose & scripting languages such as Scala/Python/R to drive innovative and impactful Search, Recommender Systems and Personalization customer experiences for KP Digital.

Some of the problems that you will work on:

• Build and tune models to deliver contextual content and information to members and physicians tosuch as relevant (third-party) health information artifacts, lifestyle change recommendations, or nutritioninformation.

• Researchand implement features for personalization and algorithms for a/b testing such as multi-armedbandits (MAB),et al.
• Conduct R&D on Knowledge Graph-enabled recommendations and real-time recommendations.

You will also: Design and interpret experiments intelligently to inform the product roadmap and own the end-to-end solution all the way to roll-out. Conduct deep dives into new research areas to solve tough customer problems. Provide technical leadership and mentorship to the data science and engineering community. Be a team player with strong empathy for our internal and external customers. Publish patents and research papers and represent KP Data Science at conferences.

In addition to the responsibilities listed below, this position is also responsible for solving client analytics problems; communicating results and methodologies; developing experimental design approaches to validate findings or test hypotheses; defining validity of information, how long information is meaningful, and relation to other information; working with data steward to ensure information is in compliance with regulatory and security policies; and qualifying where information can be stored or what information may be used in support of the use case. This position is also responsible for identifying and analyzing patterns in the volume of data supporting an initiative, data type, and speed or sudden variations in data collection; partnering with data stewards to define data quality expectation for specific use case; educating the organization both from IT and business perspectives on new approaches to testing hypotheses and statistical validation of results; helping the organization understand principles and math behind the process; and providing on-going tracking and monitoring of performance of decision systems and statistical models.

Essential Responsibilities:

• Practices self-development and promotes learning in others by proactively providing information, resources, advice, and expertise with coworkers and customers; building relationships with cross-functional stakeholders; influencing others through technical explanations and examples; adapting to competing demands and new responsibilities; listening and responding to, seeking, and addressing performance feedback; providing feedback to others; creating and executing plans to capitalize on strengths and develop weaknesses; supporting team collaboration; and adapting to and learning from change, difficulties, and feedback.
• Completes work assignments and supports business-specific projects by applying expertise in subject area; supporting the development of work plans to meet business priorities and deadlines; ensuring team follows all procedures and policies; coordinating resources to accomplish priorities and deadlines; collaborating cross-functionally to make effective business decisions; solving complex problems; escalating high priority issues or risks as appropriate; and recognizing and capitalizing on improvement opportunities.
• Executes creative data analytic approaches leading to actionable outcomes by defining and calculating metrics to be analyzed; defining, calculating, and validating algorithms; and conducting analyses, including descriptive, correlational, inferential, and/or predictive statistics.
• Develops, implements, and automates business and reporting solutions by working with stakeholders in their design, planning, and implementation while ensuring consistency and coherency; evaluating and summarizing data and results; creating summary statistics; developing data reports, visualizations, and/or interactive Business Intelligence (BI) reports; reporting to stakeholders on key findings; identifying needs for the development and implementation of additional reporting solutions; and preparing documentation as appropriate.
• Interprets data analyses by applying findings to contextual settings; and developing insights, reports, and presentations telling a compelling story to stakeholders to enable and influence decision making; and providing context related to data interpretations and/or limitations as appropriate.
• Drives strategic data-informed decisions by consulting with clients to identify and clarify key business needs; developing outcomes and process measures; translating business requirements; determining data/information needs and data collection methods; developing analysis plans; measuring the impact of business decisions on clients, customers, and/or members; working with clients and staff to identify opportunities and methods to improve efficiencies with analysis; supporting and training end-users; and documenting processes and deliverables.
• Gathers data and information on targeted variables in an established systematic fashion by validating data sources; querying, merging, and extracting data across sources; completing routine data refresh and update; developing and/or delivering tools for electronic data collection; and providing user training, support, and documentation.
• Develops analytical and/or statistical models enabling informed business decisions by determining data and analytical requirements; creating models leading to actionable insights; and testing, refining, and validating models.
• Prepares data for analytic efforts by integrating and consolidating data; ensuring data quality and accuracy; profiling data inaccuracies and recommending process improvements or system changes to enhance overall quality of the data; and cleaning and creating final data set(s) for analysis.

Minimum Qualifications:

• Minimum three (3) years machine learning experience.
• Minimum three (3) years experience working with data visualization tools.
• Minimum three (3) years programming experience.
• Minimum three (3) years statistical analysis and modeling experience.
• Minimum one (1) year experience in a leadership role with or without direct reports.
• Bachelors degree in Mathematics, Statistics, Engineering, Social/Physical/Life Science, Business, or related field and Minimum five (5) years experience in data analytics or a directly related field. Additional equivalent work experience in a directly related field may be substituted for the degree requirement.

Preferred Qualifications:

• Two (2) years experience delivering presentations to management.
• Three (3) years text analytics experience.
• Three (3) years deep learning experience.
• Three (3) years machine learning experience.
• Experience working with graph data models (RDF, Property), databases (Amazon Neptune, Neo4J, TigerGraph), or graph query languages (Gremlin, SPARQL, Cypher) is a plus

Primary Location: Georgia,Atlanta,Pershing Point Plaza IT
Scheduled Weekly Hours: 40
Shift: Day
Workdays: Mon, Tue, Wed, Thu, Fri
Working Hours Start: 08:00 AM
Working Hours End: 04:00 PM
Job Schedule: Full-time
Job Type: Standard
Employee Status: Regular
Employee Group/Union Affiliation: NUE-IT-01|NUE|Non Union Employee
Job Level: Individual Contributor
Specialty: Data Analytics & Reporting
Department: KPIT ADMIN - KPD CAS CNOE - 9601
Travel: No Kaiser Permanente is an equal opportunity employer committed to a diverse and inclusive workforce. Applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), age, sexual orientation, national origin, marital status, parental status, ancestry, disability, gender identity, veteran status, genetic information, other distinguishing characteristics of diversity and inclusion, or any other protected status.