Director Data Science and Analytics

Come join our amazing team and work from home!

The Data Science and Analytics Director will build and influences the future of data science at the Carrington family of companies, acts as sophisticated analytics leader and advisor to the business. Responsible for developing and leading the data analytics function to identify, structure, and help develop strategic initiatives for the company. Responsible for identifying, scoping, and translating business problems into applied statistical, machine learning, simulation, and optimization solutions to inform actionable business insights and drive business value through automation, revenue generation, and expense and risk reduction. Advises senior management on the potential impact of new and existing data-driven initiatives. Perform all duties in accordance with the company’s policies and procedures, all US state and federal laws and regulations, wherein the company operates. The target pay range for this position is $150,000.00-$175,000.00 Annually + Annual Bonus.

What you'll do:

• Provide management visibility into data-driven learnings that reveal KPI’s and influence strategic direction for the company’s lines of business.
• Advises senior management on the potential impact of new and existing data-driven initiatives.
• Computes, analyzes, and interprets complex statistical data models, working with large data sets and advanced techniques; interprets findings and makes recommendations to top management.
• Identifies, scopes, and manages sophisticated analytical projects in collaboration with business leaders, translating results to non-technical business executives.
• Develops insights into consumer behavior using predictive analytics and accurately forecast behavior to drive customer retention and other key customer metrics.
• Champions and manages efforts to deliver business insights via automated solutions using machine learning, simulation, and optimization.
• Applies a broad variety of statistical concepts (e.g., regressions, A/B tests, clustering, probability, correlation) to business problems and adapts/combines approaches to identify trends.
• Identifies and works with technology to integrate new data sources for models and graphs to augment predictive power and improve business performance.
• Collaborates with cross-functional teams to understand challenging analytical questions and identifies opportunities for leveraging company data to drive business solutions.
• Provide in-depth technical expertise for both tactical and operational initiatives.
• Design and implement AI solutions using Microsoft Azure AI services and other AI platforms.
• Implement best practices for AI model deployment, monitoring, and maintenance.
• Ensures risks associated with business activities are effectively identified, measured, supervised, and controlled in accordance with risk and compliance policies and procedures.
• Responsible for ensuring all modeling and machine learning solutions adhere to industry standards, model risk policy, and regulatory expectations as appropriate.

What you'll need:

• Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, or other similar quantitative field required; an additional 4 years of experience in statistics, mathematics, quantitative analytics, or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.
• Master’s degree or equivalent experience in a technical or statistical discipline preferred.
• 5+ years in predictive modeling, model governance, machine learning and large data analysis required.
• Previous experience in a financial services company required. 
• Experience in the mortgage/real estate industry is preferred.

Plus, you'll need:

• Expert knowledge of best practices in statistical and data science methods and high comfort working with large, unstructured data sets.
• Expert skills in regression modeling, multi variant analysis, data mining, and correlation
• Strong quantitative skills and experience with analytical methods and technology
• Strong Artificial Intelligence knowledge, particularly using Microsoft Azure AI services. 
• Ability to compute, analyze, and interpret complex statistical data and/or to develop forecasts and computer models.
• Extensive knowledge of credit models, pricing models, and predictive analytics.
• Strong problem-solving skills with an emphasis on product development.
• Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
• Knowledge of a variety of machine learning techniques (clusteri