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Senior Data Scientist

Greenboxcapital · Remote · Active · BambooHR

Job facts

FieldValue
CompanyGreenboxcapital
TitleSenior Data Scientist
Normalized title-
Department / teamRisk and Analytics
LocationUnited States
Work modelRemote / Remote
Employment typeFull Time
Salary-
Statusactive
ATS providerBambooHR
Posted / first seen2026-06-04 / 2026-05-30
Changed / last seen2026-06-06 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Greenboxcapital.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through BambooHR.Open
Provider filtered searchThe same provider as a filtered job collection.Open
Department jobsActive postings in Risk and Analytics.Open
Work model jobsActive Remote postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyGreenboxcapital
Source97b39809-a151-4208-aa4d-32b80feb4fa4
ATS providerBambooHR

Description

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

Full job record

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Org ID58098d1d-e345-4061-8576-b9d07a1907a4
Source ID97b39809-a151-4208-aa4d-32b80feb4fa4
Board ID97b39809-a151-4208-aa4d-32b80feb4fa4
Providerbamboohr
Provider Job Key164
TitleSenior Data Scientist
Normalized Title
Statusactive
Activeyes
Location Text
DepartmentRisk and Analytics
Team
Employment Typefull_time
Workplace Typeremote
Remote Policyremote
CountryUnited States
Region
City
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://greenboxcapital.bamboohr.com/careers/164
Apply URLhttps://greenboxcapital.bamboohr.com/careers/164
First Seen At2026-05-30 06:01:01Z
Last Seen At2026-06-06 10:23:31Z
Last Checked At2026-06-06 10:23:31Z
Last Changed At2026-06-06 10:23:31Z
Inactive At
Source Posted At2026-06-04 00:00:00Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=bamboohr/board=greenboxcapital/date=2026-06-06/2026-06-06T10-23-30-375Z-7bc1169ce23227eda8ab6f43b09b324af2a10a7ee7c98faf26267315594b07a5.json
Event Fields
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    "description": "<p><span style=\"font-size: 14pt\"><span style=\"font-weight: bold\">Senior Data Scientist</span> (</span><span style=\"font-size: 12pt\">United States - Remote)</span></p>\n<p><br></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">Why this Role Matters:</span></p>\n<p>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.</p>\n<p><br></p>\n<p>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.</p>\n<p><br></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">What Success Looks Like:</span></p>\n<p>Here’s how your time might break down (actual time can shift depending on business needs):</p>\n<ul>\n<li>Model accuracy and predictive performance impacting credit decisions</li>\n<li>Business impact through conversion rate, revenue growth, and risk-adjusted profitability</li>\n<li>Effectiveness of experimentation (A/B testing and causal inference insights)</li>\n<li>Reliability and scalability of production models</li>\n</ul>\n<p><span style=\"font-size: 14pt\"> </span></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">How you’ll be measured:</span></p>\n<p><span style=\"font-weight: bold\">Data Science Strategy &amp; Model Development</span></p>\n<ul>\n<li>Design, build, and deploy predictive models that directly impact credit, risk, and product performance</li>\n<li>Apply causal inference and experimentation to improve model and business outcomes</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Cross-Functional Collaboration &amp; Business Impact</span></p>\n<ul>\n<li>Partner with product, risk, and leadership teams to translate business needs into data-driven solutions</li>\n<li>Communicate insights clearly to influence strategic decisions</li>\n</ul>\n<p> </p>\n<p><span style=\"font-weight: bold\">Model Deployment &amp; Data Infrastructure</span></p>\n<ul>\n<li>Support production deployment and ongoing optimization of models</li>\n<li>Monitor performance and continuously improve model accuracy and reliability</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">You’re a Strong Fit if You:</span></p>\n<ul>\n<li><span style=\"font-size: 12pt\">Have demonstrated ability to analyze complex problems and deliver data-driven solutions with measurable impact</span></li>\n<li><span style=\"font-size: 12pt\">Bring strong ownership and accountability in a fast-paced, growth-oriented environment</span></li>\n<li><span style=\"font-size: 12pt\">Are naturally curious and continuously seek to improve models, systems, and processes</span></li>\n<li><span style=\"font-size: 12pt\">Communicate complex ideas clearly to both technical and non-technical audiences</span></li>\n<li><span style=\"font-size: 12pt\">Collaborate effectively across global, cross-functional teams</span></li>\n<li><span style=\"font-size: 12pt\">Exhibit a growth mindset and adaptability when working with evolving data and business needs</span></li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">What You’ve Done Before:</span></p>\n<ul>\n<li><span style=\"font-size: 12pt\">Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, or related field required; advanced degree (MS, PhD, or MBA) preferred</span></li>\n<li><span style=\"font-size: 12pt\">8+ years of experience in data science, predictive modeling, and financial analytics</span></li>\n<li><span style=\"font-size: 12pt\">Proven success developing and deploying machine learning models in FinTech or financial services</span></li>\n<li><span style=\"font-size: 12pt\">Experience in merchant cash advance, revenue-based financing, or alternative small business lending (strongly preferred)</span></li>\n<li><span style=\"font-size: 12pt\">Experience working in startup or high-growth environments and scaling systems</span><br></li>\n</ul>\n<p><br><br></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">Tools and Expertise You’ll Bring:</span></p>\n<ul>\n<li>Advanced proficiency in Python for model development and system design</li>\n<li>Strong experience with SQL and large-scale data analysis</li>\n<li>Deep expertise in statistical modeling, machine learning, and feature engineering</li>\n<li>Experience designing and analyzing A/B tests and applying causal inference methods</li>\n<li>Experience with model deployment, monitoring, and lifecycle management</li>\n<li>Familiarity with Databricks, MLflow, and modern MLOps practices</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">What to Expect from Our Interview Process</span></p>\n<p>We believe in a respectful, efficient, and transparent hiring experience. Here’s what you can typically expect:</p>\n<p><br><br></p>\n<p><span style=\"font-weight: bold\">Step 1: Initial Phone Screen (30 minutes)</span><br>A brief conversation with a recruiter to learn more about your background, interests, and alignment with the role.</p>\n<p><span style=\"font-weight: bold\">Step 2: Hiring Manager Interview (1 hour)</span><br>A deeper discussion about the role, your relevant experience, and how you’d contribute to the team.</p>\n<p><span style=\"font-weight: bold\">Step 3: Role-Specific Assessment or Panel Interview (1 hour)</span><br>Depending on the role, this may include a take-home assignment, technical interview, or live case study with team members.</p>\n<p><span style=\"font-weight: bold\">Step 4: Final Interview or Leadership Chat (1 hour)</span><br>A final conversation with senior leadership or cross-functional team members to ensure alignment with our mission and values.</p>\n<p><span style=\"font-weight: bold\">Step 5: Offer &amp; Background Check</span><br>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.</p>\n<p><br></p>\n<p><span style=\"font-size: 14pt; font-weight: bold\">Benefits:</span></p>\n<p><span style=\"font-size: 12pt\">💸 Competitive Pay - We know your worth and we pay accordingly.</span></p>\n<p><span style=\"font-size: 12pt\">🌴 Flexible PTO - Work hard, rest well. Take the time you need to recharge.</span></p>\n<p><span style=\"font-size: 12pt\">🏡 Remote - Fully remote within the U.S., working Eastern Time hours to keep everyone aligned.</span></p>\n<p><span style=\"font-size: 12pt\">🩺 Full Benefits Package - Health, dental, vision, 401K with employer match</span></p>\n<p><span>🧠 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</span></p>\n<p> </p>",
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