Lead Data Scientist

Location

Charleston - 997 Morrison Drive, Suite 402

Business

We are a leader in the single-family rental (SFR) Aggregation space with over 10,000 homes across the Southeast and Midwest. Maymont Homes was founded in 2011 to bring technology to the single-family rental space. Over the years we have become a full-service acquisition, renovation, and property management company growing throughout the South and Midwest. By the application of efficient processes enabled by advanced software, our company can provide clean, safe, affordable housing to thousands of people. We strive to offer better living opportunities for individual families, which ultimately improve the lives in the communities we serve!

Job Description

Overview
The primary mission of the Lead Data Scientist role is to help our business evolve into an insights-driven organization. The position sits in our Analytics and Data Science team, which aims to disrupt our industry with emerging technologies and data science solutions that drive sustainable competitive advantage for Maymont Homes. The Lead Data Scientist will provide critical analytics to the business, develop deployable machine learning models to provide insights and recommendations to the business to improve internal operations, to understand customers, to provide smarter products and services, to create additional revenue, and to drive decision making. This role will help lay the enterprise-ready foundation for data science across Maymont Homes.
Responsibilities

• Formulate Data Science Problems: Collaborate with cross-functional teams, including asset management, construction, marketing, leasing, and finance, to identify business problems and opportunities where data science and machine learning, including generative AI, can add value.
• Lead data science projects: Design and execute end-to-end data science projects, from problem definition and data collection/preparation to statistical analysis and modeling, interpretation of results, and development of actionable insights and recommendations.
• Statistical modeling and machine learning: Utilize statistical techniques, machine learning algorithms, and generative AI approaches to develop algorithms and uncover patterns, develop predictive models, and create data-driven solutions for various business challenges. Perform basic research to understand what methodologies and practices are commonly used for specific business-related problems.
• AutoML/Data Science Tooling: Be comfortable exploring and using advances in AutoML and other augmentative technologies to expedite model development and validation.
• Establish a strong machine learning foundation: Work closely with our IT operations team to build and maintain a robust machine learning infrastructure, frameworks, and pipelines, ensuring data quality, scalability, monitoring, reproducibility, and efficiency in model development and deployment.
• Experimentation: Generate hypotheses, design and execute experiments, analyze and interpret results, , and effectively communicate findings and recommendations to technical and non-technical audiences.
• Data management and governance: Ensure the consistency, accuracy, and quality of data used in modeling and analysis, working closely with data engineers and data architects to implement data governance best practices. Identify and design testing of novel data sets that can be leveraged by the business to improve operations and profitability.
• Communicate Insights: Extract meaningful insights from large datasets and communicate findings to both technical and non-technical stakeholders through visualizations, presentations, and reports.
• Collaborate with teammates: Collaborate by providing guidance and expertise in statistical and analytical techniques, as well as machine learning methodologies, to technical team members including data engineers and data analysts.
• Stay up to date with advancements in data science: Continuously enhance your knowledge of the latest trends, tools, and techniques in data science, machine learning, and predictive analytics, and apply them to improve our data-driven capabilities.
• Collaborate with external partners: Engage with external partners, including vendors, research institutions, and industry experts, to explore opportunities for innovation, access to additional data sources, and collaboration on cutting-edge projects related to generative AI and machine learning.
   

Qualifications

• A bachelor’s degree in Computer Science, Mathematics, Statistics, Engineering or a related quantitative field is required. A master’s or PhD in Data Science, Machine Learning, or a related field is preferred.
• Work experience: At least 7 years of experience working as a Data Scientist/Analyst on data science applications, with a proven track record of leading successful data science projects. Prior experience in implementing predictive modeling and building a strong machine learning foundation is required. Prior experience in the finance industry is highly desirable with experience in home building or real estate industry being a plus.

• Strong analytical skills: Demonstrated expertise in data analysis, statistical modeling, and machine learning techniques. Experience with tools and programming languages such as Python, R, SQL, and PowerBI data visualization tool is essential.
• Project Leadership abilities: Proven experience in leading data science projects end-to-end, mentoring junior data scientists or data analysts along the way. Strong communication and interpersonal skills are required to effectively collaborate with cross-functional teams and senior stakeholders.
• Business acumen: Understanding of the finance or real estate industry and the ability to translate business problems into data-driven solutions. Familiarity with asset risk management, scheduling optimization, pricing optimization, financial forecasting, customer segmentation, and demand forecasting is important.
• Problem-solving mindset: Ability to think critically, identify patterns, and creatively apply analytical techniques, to solve complex business challenges.
• Data governance and ethics: Familiarity with data management principles and best practices, including data quality, data privacy, and ethical considerations of working with sensitive data.
• Flexibility and adaptability: Willingness to adapt to a fast-paced and rapidly changing environment. Demonstrated ability to manage multiple projects simultaneously, prioritize tasks, and meet deadlines.
• Technologies and Methodologies:
  • Proficiency in building data pipelines to feed ML/NLP models
  • Strong adherence to core software engineering principles (code modularization, versioning, git, testing etc.)
  • Understanding of key statistical analysis principles and how to apply them in a business environment.
  • Proficiency in using Jupyter Notebooks and Python virtual environments
  • Proficiency in machine learning frameworks such as scikit-learn, TensorFlow, Spark
  • Proficiency in SQL and RDBMS
  • Proficiency in cloud technologies and their application to data science.
  • Proficiency using AWS RedShift and SageMaker

Why work for Maymont Homes ​?

Our Mission – “We Positively Impact the Lives in the Communities We Serve”. We do this through the work we do and the volunteer efforts that the company sponsors. You can make a difference in your community while you work!

Outstanding benefits package – our benefits are provided by Brookfield and offer immediate 5% match on the 401(k) plan, wellness credits that significantly reduce the employee cost for health care coverage, and up to 160 hours of PTO per year for full time employees.

Huge parent company – support and backing from Brookfield Asset Management, one of the largest real estate asset management companies.

Career growth – with our plans for growth and expansion into new markets, there are many opportunities to move up within the company.

Equal Opportunity Employer: Minorities/Religion/Sex/Protected Veterans/Disability/Sexual Orientation/Gender Identity/Marital Status/Pregnancy/Age/National Origin/Genetic Information. #MYMT