Lead Decision Science Analyst

Role Overview

• Leverages expert business, analytical and technical knowledge to lead discussions with cross functional teams to understand and collaborate highly complex business objectives and influence solution strategies.
• Applies advanced analytical techniques to solve business problems that are typically large scale with significant impact to current and/or future business strategy.
• Organizes and leads all aspects of the development of requirements/resources necessary to meet established objectives.
• Applies innovative and scientific/quantitative analytical approaches to draw conclusions and make recommendations to answer the business objective and drive the appropriate change.
• Translates recommendation into communication materials to effectively present to all levels of management.
• Incorporates visualization techniques to support the relevant points of the analysis and ease the understanding for less technical audiences.
• Identifies and gathers the relevant and quality data sources required to fully answer and address the problem for the recommended strategy through testing or exploratory data analysis (EDA).
• Integrates/transforms disparate data sources and figures out appropriate data hygiene techniques to apply.
• Thoroughly documents assumptions, methodology, validation and testing to facilitate peer reviews and compliance requirements.
• Monitors, understands and adopts emerging technology that can affect the application of scientific methodologies and/or quantitative analytical approaches to problem resolutions.
• Succinctly delivers complex analysis/findings in a manner that conveys understanding, influences senior executives, garners support for recommendations, drives business decisions, and influences business strategy.
• Provides subject matter expertise in operationalizing recommendations.
• Researches and pursues the latest and/or industry leading practices in data and analytics, (Ex: Cloud, Data Mining, Python, Neural Networks, Sensor data, IoT, Streaming/NRT data) to advance the overall DSA community knowledge.
• Finds opportunities to continue to learn in the data and analytics space, whether informal (E.g., Coursera, Udemy, Kaggle, Code Up, etc) or formal (E.g. Certifications or advanced coursework).).
• Innovates to create new and emerging data sets, and incorporation (data wrangling, data munging) into new insights.
• Ensures risks associated with business activities are effectively identified, measured, monitored, and controlled in accordance with risk and compliance policies and procedures.

Requirements

• Bachelor's degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative field is required; OR 4 years of related statistics, mathematics or quantitative analytics or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.
• 8 years of data & analytics experience; OR 6 years of data & analytics experience and up to 2 years of progressive functional business relevant experience within the respective industry of responsibility (i.e. P&C, Bank, Finance, Marketing etc.) for a total of 8 years combined experience; OR Advanced degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative field and 6 years of experience in data/analytics or functional business experience within the respective industry of responsibility (i.e. P&C, Bank, Finance, Marketing, etc.).
• 3 years of direct and/or indirect management experience.
• Demonstrates expert skills in mathematical and statistical techniques and approaches used to drive fact-based decision-making.
• Experienced knowledge of data analysis tools, data visualization, developing analysis queries and procedures in SQL, SAS, BI tools or other analysis software, and relevant industry data & methods and ability to connect external insights to business problems.

Tech Stack

• Cloud
• IoT
• Python
• SQL

Benefits

• comprehensive medical, dental and vision plans
• 401(k)
• pension
• life insurance
• parental benefits
• adoption assistance
• paid time off program with paid holidays plus 16 paid volunteer hours
• various wellness programs
• career path planning and continuing education