Senior Data Scientist

Organizational Overview:

The National Association of REALTORS® (NAR) is a team of professionals dedicated to providing world-class service to over 1.5 million REALTORS® working in the United States and around the world. The real estate industry is fast-paced and fast-changing--each year, our members participate in the sale, lease, and management of billions of dollars in real estate. As in every industry, our members’ value proposition is constantly being challenged by innovation.

It is our mission to help REALTORS® navigate that change and thrive in their careers. We cannot do that without the ideas, passion, and commitment from our talented employees. As our greatest assets, employees are offered their pick of competitive benefits/perks and flexible work options. NAR is certified as a Great Place to Work®. Our most successful employees are committed to our Core Values, which are:

Putting Members First
Leading Change
Advancing Diversity and Inclusion
Giving Respect
Collaborating
Communicating

Location: This position is located in the Chicago, IL or Washington, DC office only

Position Summary:

NAR’s IT Data Science team is looking for a highly motivated Senior Data Scientist to join our growing team and make their mark. We are currently on a transformation journey and providing accurate and actionable insights to our customers is a key goal we have set out to achieve. The Senior Data Scientist will play a lead role in our modernization journey. The ideal candidate will have a desire to work cross functionally, roll up their sleeves and analyze sophisticated business processes and ideas and create innovative solutions. They will have autonomy and the ability to collaborate with their team members, business colleagues, and customers and become part of a dynamic team. This role will require advanced quantitative, analytics, data mining and manipulation skills while also taking ownership of projects from start to finish.

Duties and Responsibilities:

• Work with business stakeholders, understand their needs and develop innovative analytical solutions.
• Enhance the data science domain at NAR with expertise, prior knowledge, and experience
• Mentor junior data scientists and create data science domain awareness among peers and customers
• Assist in the scoping and development of new analytical initiatives
• Collect, connect, and preprocess relevant structured and unstructured data from disparate sources, including internal databases, open data platforms, and third-party providers
• Perform exploratory data analysis (EDA), generate and test working hypotheses, and uncover interesting trends and relationships in membership data, particularly in the context of increasingly difficult open-ended questions
• Develop statistical analyses and build machine learning models that help explain and predict trends along dimensions of membership growth, retention, and engagement
• Design and integrate visualizations in comprehensive dashboards that enable key stakeholders to monitor and react to important membership trends
• Stitch together a comprehensive and compelling story that helps describe analytical results and strengthen insight-driven decision-making
• Support ad hoc analytical requests from colleagues in the group
• Assist in the acquisition and integration of new data sources into the data lake
• Interact more hands on with external clients, collaborate with stakeholders, and take ownership of projects from start to finish
• Ability to work with disparate data sets and fuse them to create research papers, dashboards, and deliverables
• Keep up to date with the latest news and innovations within Data Science and adjacent fields to ensure projects and visions stay relevant

Qualifications:

• Bachelor's or Master’s degree in Computer Science, Economics, Statistics or a related field
• 3 to 5 years of relevant experience as a Data Analyst, Data Scientist, or another analytical-oriented position is required
• 3 to 5 years of experience coding in Python, R, or Scala
• 3 to 5 years of experience with data processing (ETL) and traditional structured databases like SQL or Oracle
• 4 to 6 years of experience building supervised and unsupervised machine learning methods and deploying into production (i.e. regression models, random forests, NLP, visual recognition, clustering)
• Experience with data visualization tools such as Power BI, Tableau, matplotlib, or ggplot
• Experience with Azure or AWS AI tools and services, ML platforms and frameworks
• Familiarity with schema-less database systems like MongoDB and Elasticsearch is a plus
• Strong familiarity with software engineering best practices, data engineering, and ETL is a plus
• Independently create documentation for new data projects and requests and build collaborations within the organization
• Be able to explain tough technical insights to non-technical stakeholders
• Passion for solving problems using open-source technology is a plus
• Good communication skills, as well as an interest in working within a team environment