Senior Data Scientist

Posted 21 Days Ago
Hiring Remotely in United States
Remote
Senior level
Fintech • Financial Services
The Role
As a Senior Data Scientist at Greenbox Capital, you'll build and scale predictive models, impact credit decisions, and collaborate across teams for data-driven solutions.
Summary Generated by Built In

Senior Data Scientist (United States - Remote)

Why this Role Matters:

At Greenbox Capital, we help small businesses thrive by providing fast, accessible funding. As a Senior Data Scientist, you’ll play a key role in building and scaling the predictive models that power our credit decisioning, risk management, and fraud prevention strategies. Your work will directly influence how we evaluate opportunities, optimize profitability, and deliver smarter, faster decisions to our customers.

You’ll drive results across machine learning, experimentation, and data-driven strategy, helping us continuously improve our products and operations. This role reports to the VP of Technology and is a critical contributor to our data science function and overall growth strategy.

What Success Looks Like:

Here’s how your time might break down (actual time can shift depending on business needs):

  • Model accuracy and predictive performance impacting credit decisions
  • Business impact through conversion rate, revenue growth, and risk-adjusted profitability
  • Effectiveness of experimentation (A/B testing and causal inference insights)
  • Reliability and scalability of production models

 

How you’ll be measured:

Data Science Strategy & Model Development

  • Design, build, and deploy predictive models that directly impact credit, risk, and product performance
  • Apply causal inference and experimentation to improve model and business outcomes

Cross-Functional Collaboration & Business Impact

  • Partner with product, risk, and leadership teams to translate business needs into data-driven solutions
  • Communicate insights clearly to influence strategic decisions

Model Deployment & Data Infrastructure

  • Support production deployment and ongoing optimization of models
  • Monitor performance and continuously improve model accuracy and reliability

You’re a Strong Fit if You:

  • Have demonstrated ability to analyze complex problems and deliver data-driven solutions with measurable impact
  • Bring strong ownership and accountability in a fast-paced, growth-oriented environment
  • Are naturally curious and continuously seek to improve models, systems, and processes
  • Communicate complex ideas clearly to both technical and non-technical audiences
  • Collaborate effectively across global, cross-functional teams
  • Exhibit a growth mindset and adaptability when working with evolving data and business needs

What You’ve Done Before:

  • Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, or related field required; advanced degree (MS, PhD, or MBA) preferred
  • 8+ years of experience in data science, predictive modeling, and financial analytics
  • Proven success developing and deploying machine learning models in FinTech or financial services
  • Experience in merchant cash advance, revenue-based financing, or alternative small business lending (strongly preferred)
  • Experience working in startup or high-growth environments and scaling systems

Tools and Expertise You’ll Bring:

  • Advanced proficiency in Python for model development and system design
  • Strong experience with SQL and large-scale data analysis
  • Deep expertise in statistical modeling, machine learning, and feature engineering
  • Experience designing and analyzing A/B tests and applying causal inference methods
  • Experience with model deployment, monitoring, and lifecycle management
  • Familiarity with Databricks, MLflow, and modern MLOps practices

What to Expect from Our Interview Process

We believe in a respectful, efficient, and transparent hiring experience. Here’s what you can typically expect:

Step 1: Initial Phone Screen (30 minutes)
A brief conversation with a recruiter to learn more about your background, interests, and alignment with the role.

Step 2: Hiring Manager Interview (1 hour)
A deeper discussion about the role, your relevant experience, and how you’d contribute to the team.

Step 3: Role-Specific Assessment or Panel Interview (1 hour)
Depending on the role, this may include a take-home assignment, technical interview, or live case study with team members.

Step 4: Final Interview or Leadership Chat (1 hour)
A final conversation with senior leadership or cross-functional team members to ensure alignment with our mission and values.

Step 5: Offer & Background Check
If it’s a mutual fit, we’ll move forward with background check and present a competitive offer. We aim to complete this process within 2–3 weeks from your first conversation with us.

Benefits:

💸 Competitive Pay - We know your worth and we pay accordingly.

🌴 Flexible PTO - Work hard, rest well. Take the time you need to recharge.

🏡 Remote - Fully remote within the U.S., working Eastern Time hours to keep everyone aligned.

🩺 Full Benefits Package - Health, dental, vision

🧠 Smart, Supportive Teammates - Collaborate with sharp minds who are kind, driven and uphold our core values!


Skills Required

  • Bachelor's degree in Data Science, Computer Science, Mathematics, Statistics, or related field
  • 8+ years of experience in data science, predictive modeling, and financial analytics
  • Proven success developing and deploying machine learning models in FinTech or financial services
  • Experience in merchant cash advance, revenue-based financing, or alternative small business lending
  • Experience working in startup or high-growth environments and scaling systems
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The Company
HQ: Miami, FL
88 Employees
Year Founded: 2012

What We Do

Greenbox Capital is a place for people who want to move quickly, solve meaningful problems, and take real ownership of their work. We help small businesses access the capital they need to grow, and we're building the team to take that mission further.

Why Work With Us

At Greenbox, we believe the best work happens when people are trusted, challenged, and empowered to think beyond their job description. We move fast, ask hard questions, and take responsibility for outcomes, not just effort. You won’t find layers of red tape or performative culture here. Instead, you’ll find people who care deeply about the work,

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