Data Scientist Lead

Progress Residential•Tempe, AZ

33d

About The Position

Your career has a home here. Ready to make an impact with a dynamic, forward-thinking company? As a leading property manager of single-family rental homes nationwide, we take great pride in creating an enjoyable living experience for our residents - and an empowering, people-first culture for our team members. That's why, for two years in a row, our employees have voted Progress a certified Great Place to Work. Why join Progress? As the demand for professionally managed rental homes continues to grow, so do the opportunities at Progress. We're looking for passionate professionals who are ready to grow with us, make a difference and be part of something meaningful. Want to learn more? Text "ProgressJobs" to 25000 to chat with Kate, our AI Recruiting Assistant. She can help you explore open roles, apply, and answer your questions in real time. Position Summary: As a member of the Analytics team, the Data Scientist Lead will be focused on improving the single-family rental (SFR) customer experience, increasing occupancy rates, and reducing costs on home repairs and renovations. This is a high visibility role with exposure to multiple functions within the organization. Day to day partnerships include working with his/her team and cross-functionally at the senior leadership level to understand Progress's business challenges and recommend data-driven solutions. The right candidate is naturally curious, has excellent quantitative modeling and creative problem-solving skills, an ability to partner with stakeholders to drive results, and likes working in a fast paced environment. Additionally, this person must have demonstrated the ability to execute projects end to end with minimal supervision and be able to create a compelling case for change in PowerPoint, articulating technical concepts to non-technical stakeholders at all levels including the C-suite.

Requirements

Bachelor's Degree required in a mathematics-based discipline such as engineering, math, statistics, economics or similar discipline; Master's degree preferred
10+ years of relevant data science, analytics, predictive analytics or advanced risk modeling with large-scale data and project management experience
3+ years of hands-on Python experience coding machine learning models (XGBoost, Random Forest, Catboost, etc.), time series (ARIMA, VC, etc.), regression and/or segmentation analyses on large data sets
3+ years of hands-on SQL experience, specifically to write complex, highly optimized queries across large volumes of structured and unstructured data in preparation for analyses; experience with Snowflake a plus
Experience presenting to an executive audience, building insightful presentations that use data to create compelling cases for change
Can quickly extract insights from various forms of data and succinctly guide the business on how to use them
Expert in statistics including probability theory and sampling, predictive modeling, test vs. control, and the application of these methods to solve real-world problems
Demonstrated ability to successfully build rapport with stakeholders that do not have analytical expertise, translating complex mathematical concepts into easy-to-understand terms
Ability to prioritize, multitask, manage multiple complex projects simultaneously, and deliver results within compressed timelines
A strategic and tactical thinker; strong vision and ability to think outside the box, provide innovative solutions to core business practices, execute, and implement
Self-starter, very resourceful, a quick learner with a high degree of agency, integrity and ownership
Ability to work at a fast pace, both independently and as a team, without sacrificing attention to detail
Must be comfortable hunting for, aggregating, cleaning, and validating data from multiple sources

Nice To Haves

Master's degree in quantitative discipline such as engineering, math, statistics, economics or similar discipline preferred.
Experience in portfolio/risk management and/or quantitative analysis of capital assets
Experience with bureau data
Direct knowledge or experience with advanced loan or credit scoring and predictive modeling
Experience working as a data scientist (or equivalent role/function) in a regulated industry such as financial services, healthcare, real estate, etc., where predictive models must undergo stress testing and scrutiny by a 3rd party auditor and abide by SR 11-7 guidelines
Experience with the AWS computing environments and storage services such as s3

Responsibilities

Manages Projects Independently
Establish a professional and trusting relationship with stakeholders (Director and VP level)
Lead and complete projects once given the objective and direction. Hold intake sessions, size projects, design solutions, manage scope and recalibrate work priorities as needed
Communicate regularly and effectively on project status, clarity of deliverables, and requirements
Mentor junior members of the team on projects - structure, solution builds, organizing data, etc.
Use a variety of techniques to analyze large data sets ranging from unsupervised machine learning (ex: XGBoost, CatBoost, Random Forest) to research-driven root cause. These tools will be used to highlight opportunities with Progress's key business drivers. For example, likelihood to renew, collectability scoring, predicted costs for renovations, building decision trees to support operating efficiencies for home repairs
Segment data using techniques such as Clustering (ex: k-means, KNN) and Decision Trees
Develop predictive models for these segments; conduct quantitative research and back-testing to evaluate model assumptions and develop confidence in results
Develop new analytical approaches to problem-solving at Progress, driving improvements in the quality, efficiency & rigor of insights delivered to the business; use findings to guide change
Gather and aggregate data from multiple internal and external sources. Reconcile data with known sources of truth.
Uncover patterns, identify root causes, and accurately interpret operational and financial impact
Create compelling stories with data in PowerPoint; present findings to a broad group of cross-functional leaders (all levels including C-suite), using data to drive and influence management decisions
Develop and implement process controls to mitigate business risk and to improve operating efficiency; measure performance of implemented solutions over time

Benefits

Competitive Compensation - Including performance-based bonuses that reward your contributions.
Comprehensive Benefits Package - Medical, dental, vision, parental leave, 401(k) with company match and more.
Generous Time Off - Enjoy PTO based on tenure, 10 paid holidays and 1 floating holiday.
Ongoing Learning and Development - Quarterly summits, town hall meetings and continuous training to support your professional growth.
A Culture that Celebrates You - We believe in collaboration, recognition and having fun while doing important work.

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