Senior Data Scientist, Contact Center AI

Req179615Position PurposeThe Senior Data Scientist is responsible for supporting data science initiatives that drive business profitability, increased efficiencies, improve automation using AI and improved customer experience. This role applies industry-leading Agentic AI capabilities for creatively solve business problems in the Contact Center space. Data Scientists are also responsible for ensuring that developed codes are documented into a library of reusable algorithms. Based on the specific data science team, this role would need to be knowledgeable in one or more data science specializations, such as NLP, Conversational AI, Information Retrieval, Generative AI or search.As a Senior Data Scientist, you will also be responsible for applying advanced analytics methods and algorithms for identifying trends and providing business solutions. This role is expected to present insights and recommendations to non-technical audiences and explain the benefits and impacts of the recommended solutions. In addition, Data Scientists collaborate with business partners and cross-functional teams, requiring effective communication skills, building relationships, and focus on understanding the overall business area being supported.Key Responsibilities35% Solution Development - Proficiently design and develop algorithms and models to use against large datasets to create business insights; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies; Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Prepare reports, updates and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation30% Project Management & Team Support - Work with project teams and business partners to determine project goals; Provide direction on prioritization of work and ensure quality of work; Provide mentoring and coaching to more junior roles to support their technical competencies; Collaborate with managers and team in the distribution of workload and resources; Support recruiting and hiring efforts for the team20% Business Collaboration - Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Provide general education on advanced analytics to technical and non-technical business partners; Deep understanding of IT needs for the team to be successful in tackling business problems; Actively seek out new business opportunities to leverage data science as a competitive advantage15% Technical Exploration & Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Define best practices and develop clear vision for data analysis and model productionalization; Contribute to library of reusable algorithms for future use, ensuring developed codes are documentedDirect Manager/Direct ReportsThis position reports to manager or aboveThis position has 0 Direct ReportsTravel RequirementsTypically requires overnight travel less than 10% of the time.Physical RequirementsMost of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.Working ConditionsLocated in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.Minimum QualificationsMust be eighteen years of age or older.Must be legally permitted to work in the United States.Preferred QualificationsMasters in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience 4+ years of industry experience in Machine Learning and AI (specifically Conversational AI) Prior background and experience in building Generative AI based solutions for industry is a plus Working knowledge of Microsoft Excel and Power Point Experience in a modern scripting language (preferably Python) Proficient running queries against data (preferably with Google BigQuery or SQL) Proficient utilizing statistical techniques to identify key insights that help solve business problems Knowledgeable in Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP Demonstrated experience in Machine Learning, Conversational AI, predictive modeling, data mining and data analysis Minimum EducationThe knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.Preferred EducationNo additional educationMinimum Years Of Work Experience5Preferred Years Of Work ExperienceNo additional years of experienceMinimum Leadership ExperienceNonePreferred Leadership ExperienceNoneCertificationsNoneCompetenciesAttracts Top Talent: Attracting and selecting the best talent to meet current and future business needsBusiness Insight: Applying knowledge of the business and the marketplace to advance the organization's goalsCollaborates: Building partnerships and working collaboratively with others to meet shared objectivesCommunicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiencesCultivates Innovation: Creating new and better ways for the organization to be successfulCustomer Focus: Building strong customer relationships and delivering customer-centric solutionsDevelops Talent: Developing people to meet both their career goals and the organization's goalsDirects Work: Provides direction, delegating and removing obstacles to get work doneDrives Results: Consistently achieving results, even under tough circumstancesNimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodderOptimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvementSelf-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels