Senior Staff Data Scientist

Overview 

Flex is a growth-stage, NYC headquartered FinTech company that is creating the best rent payment experience. It’s hard to believe that it’s 2024 and paying rent on time is expensive, inflexible, and difficult. We’re here to change that! Flex enables our users to pay rent throughout the month on a schedule that better fits their finances and budget. Our mission is to empower as many renters as possible with flexibility over their most significant recurring expense. After deliberately keeping a stealth profile as we built up unprecedented investor support and an enthusiastic user base, we are looking for motivated individuals to help us keep our mission growing. Will you be a part of the team?

About the role

Flex for Good empowers renters by providing timely financial support, education, and advocacy to help overcome economic challenges and achieve housing stability. This program aims to enhance renter well-being and create lasting positive change in the rental ecosystem. Our current focus is eviction prevention through targeted financial assistance, utilizing predictive analytics to optimize resource allocation and generate high-impact outcomes. By identifying at-risk households early and delivering precisely calibrated support, we aim to create sustainable housing solutions that benefit individuals, families, and communities.

We are looking for a Senior Staff Data Scientist to join our innovative team and make a significant impact by supporting Flex for Good with cutting-edge data science and machine learning solutions. As a key contributor, you will design and deploy advanced statistical and machine learning models to identify renters at risk of eviction, optimize resource allocation, and measure program outcomes. Collaborating with cross-functional teams, you will solve high-impact challenges and drive continuous innovation, ensuring we remain leaders in data-driven decision-making.

What you’ll do

• Model Development & Deployment: Design, build, and implement advanced statistical and machine learning models, focusing on prediction, optimization, and impact measurement.
• Predictive Modeling: Develop and apply sophisticated predictive models to identify high-risk targets who are most likely to benefit from rental assistance, guiding strategic decisions on resource allocation.
• Causal Inference: Create and implement causal inference models to assess and attribute outcome impact, improving the effectiveness and efficiency of our program.
• Exploratory Data Analysis (EDA): Analyze large, complex datasets to uncover key trends and generate actionable insights that drive important program decisions.
• Cross-functional Collaboration: Work closely with business stakeholders, product managers, and engineers to define problems, design modeling solutions, and ensure measurable impact.
• Model Evaluation & Testing: Conduct rigorous A/B testing, model validation, and performance evaluation to ensure that solutions align with program objectives.
• Continuous Improvement: Experiment with new techniques, fine-tune model parameters, and iterate on solutions to enhance model performance and overall program efficacy.
• Innovation: Stay at the forefront of machine learning, statistics, and optimization advancements, applying these innovations to optimize model performance.
• Effective Communication: Translate complex technical findings into clear, actionable insights for both technical and non-technical stakeholders, presenting results through intuitive visualizations and reports.
  
  

Key qualifications

• Master’s or Ph.D. in Statistics, Mathematics, Computer Science, or a related quantitative field.
• 6+ years of experience in data science, specializing in statistical modeling and machine learning applied to real-world challenges.
• Expertise in predictive modeling, optimization techniques, and causal inference to address complex business problems.
• Strong proficiency in Python, R, or similar programming languages, with deep knowledge of statistical and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Hands-on experience with large datasets, cloud platforms (e.g., AWS, GCP), or distributed computing frameworks for data processing.
• Proven track record of leveraging advanced statistical, machine learning, and data visualization techniques to drive measurable business outcomes.
• Exceptional communication skills, with the ability to articulate complex technical models and insights to both technical and non-technical audiences.
• Strong problem-solving abilities and a collaborative mindset, working effectively with cross-functional teams to develop and deploy impactful solutions.

The compensation range for this role will be commensurate with the candidate's experience and Flex's internal leveling guidelines and benchmarks.

• For working locations in NY/NJ/CA, the base salary pay range will be $209,000-$225,000
• For all other states, the base salary pay range will be $188,000-$203,000

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