TRAVEL REQUIREMENTS:

• No travel required.

PHYSICAL REQUIREMENTS:

• Most 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.

MINIMUM QUALIFICATIONS:

• Must be eighteen years of age or older.
• Must be legally permitted to work in the United States.

PREFERRED QUALIFICATIONS:

• Master’s degree in a quantitative field (Computer Science, Math, Statistics, etc.) or equivalent work experience
• 3+ years of experience in business intelligence and analytics
• Working knowledge of Microsoft Excel and Power Point
• Experience in a modern scripting language (preferably Python)
• Experience running queries against data (preferably with Google BigQuery or SQL)
• Experience in predictive modeling, data mining and data analysis
• Experience with data visualization software (preferably Tableau)
• Experience utilizing statistical techniques to identify key insights that help solve business problems
• Basic knowledge or exposure to Prescriptive Modeling like optimization, computer vision, recommendation, search or NLP
• Basic knowledge or exposure to predictive modeling, data mining and data analysis

MINIMUM EDUCATION:

• The 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 EDUCATION:

• No additional education

PREFERRED YEARS OF WORK EXPERIENCE:

• No additional years of experience

MINIMUM LEADERSHIP EXPERIENCE:

• None

PREFERRED LEADERSHIP EXPERIENCE:

• None

COMPETENCIES:

• Action Oriented: Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm
• Business Insight: Applying knowledge of the business and the marketplace to advance the organization’s goals
• Collaborates: Building partnerships and working collaboratively with others to meet shared objectives
• Communicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences
• Customer Focus: Building strong customer relationships and delivering customer-centric solutions
• Drives Results: Consistently achieving results, even under tough circumstances
• Nimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder
• Optimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvement
• Plans and Aligns: Planning and prioritizing work to meet commitments aligned with organizational goals
• Self-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels

POSITION PURPOSE:

The Associate Data Scientist is responsible for supporting data science initiatives that drive business profitability, increased efficiencies and improved customer experience. This role works closely with Data Scientists and/or Sr. Data Scientists in their team to develop solutions by applying advanced analytics methods and algorithms for identifying trends and providing business solutions. Based on the specific data science team, this role may need to develop skills in one or more data science specializations, such as optimization, computer vision, recommendation, search or NLP.
As an Associate Data Scientist, you will develop skills that effectively leverage data science methodologies to creatively solve business problems and provide strategic insights. This requires effective communication skills as well as continuous learning and development at both the technical and business level.

KEY RESPONSIBILITIES:

• 70% Solution Development - Design and develop algorithms and models to use against large datasets to create business insights; Supports data science projects by conducting effective analysis to solve business problems; Executes tasks with high levels of efficiency and quality; Consults with Data Scientist or Sr. Data Scientist on appropriate selection, utilization and interpretation of advanced analytical methodologies; Learn about the assigned business areas to provide better solutions by incorporating business-specific knowledge
• 20% Communicating Results - Effectively communicate insights and recommendations to both technical and non-technical audience; Support preparation of reports, updates and/or presentations related to progress made on a project or solution; Highlights potential impacts of recommendations to drive alignment and appropriate implementation
• 10% Technical Learning - Keep up to date on industry trends, best practices and emerging methodologies; Continually develop skills and expertise in data analytics concepts and methodologies; Identify opportunities to apply learnings