Full-Time Quantitative Analytics Manager

The Quantitative Analytics Manager is primarily responsible for leading the development and validation of predictive and machine-learning models for specific business needs using statistics, advanced mathematical techniques, and/or computer science.

Leverages advanced mathematical knowledge, analysis, partnerships, and business knowledge to provide solutions to predictive and prescriptive questions.

Projects are often broad in scope across multiple business segments and involve guiding a team and/or project.

Success factors include:

• Demonstrating leadership through strong communication skills.
• Addressing conflict and coaching others on developing technical skills.
• Managing competing priorities and presenting holistic analyses.
• Establishing a reputation as an effective and collaborative partner.
• Communicating technical theories to a non-technical audience.
• Connecting day-to-day work to the bigger picture and driving efficiency in solution delivery.

Qualifications:

• Master’s degree in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 5 years of relevant experience; or
• Bachelor’s degree in statistics, mathematics, economics, financial engineering, data sciences, predictive modeling, or other quantitative disciplines and at least 6 years of relevant experience.

Requirements:

• Understanding of best practices for capturing/retaining data.
• Pros and cons of competing analysis methods.
• Experience leading by partnering with others to anticipate and understand needs.
• Leading information practices, policies, and procedures.
• Setting standards and expectations for data analysis tools and techniques.
• Promoting increased efficiency of data analysis by advocating clearer data requirements.

Technology & Techniques:

• Advanced Microsoft Office Suite.
• SQL/NoSQL Relationship data structure.
• Selecting and retrieving data including unstructured data retrieval, archival, and ETL.
• Advanced Python/R/SAS: Databases.
• Efficient coding and strong code controls.
• Understanding of cloud-based computing and distributed computing.

Model Building & Maintenance:

• Establish standards and best practices; forecast future modeling tools/techniques.
• Identify, employ, and evangelize emerging techniques from industry/research.
• Coach others on data modeling methods/techniques.
• Facilitate sessions for complex data models.
• Assess and understand risks; develop contingency plans.
• Communicate observations to senior executives.
• Translate technical observations to a non-technical audience.

Expected Competencies:

• Leadership: Demonstrated leadership; assumes accountability for their work; proactively coaches and guides others.
• Partnering / Influencing: Ability to engage and partner at mid to senior leadership levels; established reputation as an effective and collaborative partner.
• Business Acumen: Understands LOB and KeyCorp strategy; leverages knowledge of competition to anticipate needs.
• Critical Thinking / Problem Solving: Anticipates business partner needs; advises leaders to make informed decisions.
• Communication: Excellent writing skills; develops writing skills in others; articulates broad implications of messages.

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