Greenbox Capital Logo

Greenbox Capital

Senior Data Scientist

Reposted 20 Days Ago
Remote
Hiring Remotely in United States
Senior level
Remote
Hiring Remotely in United States
Senior level
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.
The summary above was generated by AI

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, 401K with employer match

🧠 Smart, Supportive Teammates - Collaborate with sharp minds who are kind, driven and uphold our core values: Wear Green First, Pull the Thread, Move the Needle, Courage Over Comfort, Think Bold, Win Together, and Own the Outcome


Similar Jobs

2 Days Ago
In-Office or Remote
92K-164K Annually
Senior level
92K-164K Annually
Senior level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Lead end-to-end analytics on large healthcare datasets to design, develop, and evaluate predictive and prescriptive models. Advise clinical operations, communicate findings to executives, mentor others, define project requirements and priorities, and build scalable data pipelines and analyses using modern data and cloud tools to drive product and cost-optimization initiatives.
Top Skills: AirflowSparkAWSAzureAzure Data FactoryC++Databricks DltGitHadoopJavaPower BIPysparkPythonRSASScalaSQLTableauVb
6 Days Ago
Easy Apply
Remote
USA
Easy Apply
180K-212K Annually
Senior level
180K-212K Annually
Senior level
Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
Own and evolve revenue calibration models tying CX interactions to revenue, design causal inference and experimentation frameworks, build LLM-powered classification/NLP pipelines, productionize models with Analytics Engineers, define segmentation and behavioral signals, and ensure statistical rigor for executive reporting and regulatory defensibility.
Top Skills: A/B TestingCausal InferenceGeminiGenerative AiGleanLibrechatLlmMlNlp
4 Days Ago
In-Office or Remote
139K-225K Annually
Senior level
139K-225K Annually
Senior level
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
As a Senior Data Scientist, you'll lead AI risk assessments, manage compliance, and evaluate AI system behavior, ensuring safe deployment across banking use cases.
Top Skills: Adversarial TestingAIGenerative AiLarge Language ModelsLimeModel Risk ManagementPythonRisk Governance ToolsShapTransformer Models

What you need to know about the Los Angeles Tech Scene

Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.

Key Facts About Los Angeles Tech

  • Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
  • Key Industries: Artificial intelligence, adtech, media, software, game development
  • Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
  • Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account