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Data Scientist [Integrated Risk Management]

  • Salary not listed
  • Remote-friendly · fits your timezone
  • Posted last month · via Greenhouse

Develop risk models for integrated credit and fraud detection

As a Data Scientist at Plata Card, you will develop and implement risk models to support integrated risk management. Your work will focus on credit and fraud detection using data analysis and machine learning techniques. The role involves collaborating with cross-functional teams to translate insights into actionable risk strategies.

Why This Role?

Work on integrated risk management with direct impact on credit and fraud systems

Key Responsibilities

  • Develop and validate predictive models for credit risk assessment
  • Build machine learning solutions for fraud detection and prevention
  • Analyze large datasets to identify risk patterns and trends
  • Collaborate with risk and product teams to implement model insights
  • Monitor model performance and recommend improvements over time

Requirements

  • Proficiency in Python or R for statistical modeling and machine learning
  • Experience with machine learning algorithms for classification and prediction
  • Strong background in statistical analysis and risk modeling concepts
  • Ability to work with large datasets and data manipulation tools
  • Experience in credit risk, fraud detection, or financial services domain

Required Skills

data sciencemachine learningdata analysisrisk managementpythonstatistical modelingrisk analysis

Indonesia Context

Working Hours Overlap:
Flexible — work your own hours
See remote (USD) vs local pay →
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Original description from Greenhouse Boards

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data-artboard-proxy-min-height="246" data-artboard-proxy-max-height="246"> <div class="t396__elem tn-elem tn-elem__8559900041712751011017" data-elem-id="1712751011017" data-elem-type="text" data-field-top-value="76" data-field-left-value="271" data-field-height-value="130" data-field-width-value="636" data-field-axisy-value="top" data-field-axisx-value="left" data-field-container-value="grid" data-field-topunits-value="px" data-field-leftunits-value="px" data-field-heightunits-value="px" data-field-widthunits-value="px" data-field-textfit-value="autoheight" data-field-top-res-320-value="73" data-field-left-res-320-value="10" data-field-width-res-320-value="306" data-field-top-res-480-value="72" data-field-left-res-480-value="80" data-field-width-res-480-value="319" data-field-top-res-640-value="56" data-field-left-res-640-value="66" data-field-width-res-640-value="501" data-field-top-res-960-value="76" data-field-left-res-960-value="152" data-fields="top,left,width,height,container,axisx,axisy,widthunits,leftunits,topunits"> <div class="tn-atom"> <div id="rec855990004" class="r t-rec" data-animationappear="off" data-record-type="396"> <div class="t396"> <div class="t396__artboard rendered" data-artboard-recid="855990004" data-artboard-screens="320,480,640,960,1200" data-artboard-height="246" data-artboard-valign="center" data-artboard-upscale="grid" data-artboard-height-res-320="363" data-artboard-height-res-480="356" data-artboard-height-res-640="241" data-artboard-height-res-960="246" data-artboard-proxy-min-offset-top="0" data-artboard-proxy-min-height="246" data-artboard-proxy-max-height="246"> <div class="t396__elem tn-elem tn-elem__8559900041713519411346" data-elem-id="1713519411346" data-elem-type="text" data-field-top-value="40" data-field-left-value="271" data-field-height-value="20" data-field-width-value="656" data-field-axisy-value="top" data-field-axisx-value="left" data-field-container-value="grid" data-field-topunits-value="px" data-field-leftunits-value="px" data-field-heightunits-value="px" data-field-widthunits-value="px" data-field-textfit-value="autoheight" data-field-top-res-320-value="40" data-field-left-res-320-value="10" data-field-width-res-320-value="261" data-field-top-res-480-value="40" data-field-left-res-480-value="81" data-field-width-res-480-value="318" data-field-top-res-640-value="29" data-field-left-res-640-value="60" data-field-width-res-640-value="307" data-field-top-res-960-value="40" data-field-left-res-960-value="152" data-fields="top,left,width,height,container,axisx,axisy,widthunits,leftunits,topunits"> <div class="tn-atom"> <p class="isSelectedEnd">We are looking for a<strong> Data Scientist</strong> for our <strong>Integrated Risk Management team</strong> to help develop risk models and analytical frameworks that support key business decisions across credit, financial, and operational risk domains. In this role, you will work on complex quantitative challenges, build predictive and diagnostic models, and partner with stakeholders across the organization to improve risk visibility, portfolio performance, and decision-making.</p> <h4>Challenges that await you:</h4> <ul data-spread="false"> <li>Develop and implement advanced statistical models for our credit portfolio at both per-account and aggregate levels to predict behavior and optimize performance</li> <li>Create sophisticated Net Present Value (NPV) models and their core components on a per-account basis for our various credit products</li> <li>Model critical financial metrics, including FX position, liquidity, reserves, and other balance sheet items to support robust financial management</li> <li>Analyze and model not only expected outcomes but also their deviations, distributions, and uncertainty, recognizing the inherently probabilistic nature of financial and risk data</li> <li>Design diagnostic and forecasting models that help identify, monitor, and mitigate risks across the organization</li> <li>Partner with cross-functional stakeholders to investigate model performance, understand deviations from expectations, and improve decision-making processes</li> <li>Contribute to the development of quantitative methodologies and risk frameworks across credit, financial, and operational risk domains</li> </ul> <h4>What makes you a great fit:</h4> <ul data-spread="false"> <li>M.S. or Ph.D. in a quantitative field such as Statistics, Computer Science, Mathematics, Physics, Economics, or a related discipline</li> <li>4+ years of hands-on experience in Data Science, Quantitative Analytics, Risk Modeling, or a similar role</li> <li>Strong understanding of statistical modeling, probability theory, and uncertainty quantification</li> <li>Experience developing predictive models and working with financial, risk, or other highly stochastic datasets</li> <li>Strong proficiency in Python or R and experience with statistical and analytical libraries (e.g., Pandas, NumPy, SciPy, Statsmodels, Scikit-learn)</li> <li>Experience with classical statistical methods, forecasting techniques, and modern machine learning approaches when appropriate</li> <li>Experience modeling distributions, confidence intervals, and risk metrics rather than focusing solely on point estimates</li> <li>Strong problem-solving skills and ability to independently drive analytical initiatives from problem definition to implementation</li> <li>Excellent communication skills with the ability to explain complex concepts to both technical and non-technical stakeholders</li> </ul> <h4>Our ways of working:</h4> <ul data-spread="false"> <li>Innovative Spirit: a commitment to creativity and groundbreaking solutions</li> <li>Honest Feedback: valuing open, transparent communication</li> <li>Supportive Team: a strong, collaborative community</li> <li>Celebrating Achievements: recognizing our wins together</li> <li>High-Tech Environment: a team of smart and ambitious people who challenge the status quo of traditional finance</li> </ul> <h4>Our benefits:</h4> <ul data-spread="false"> <li>Relocation support to one of our hubs — Mexico, Cyprus, Spain, Serbia, or Georgia — with assistance for the employee and their family</li> <li>Work remotely from anywhere, provided you can maintain overlap with the first half of the business day in Mexico</li> <li>Healthcare Coverage</li> <li>Education Budget: language lessons, professional training, and certifications</li> <li>Wellness Budget: mental health and fitness activity reimbursements</li> <li>Vacation policy: 20 days of annual leave and paid sick leave</li> </ul> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div>

Salary Context

Similar Data & Analytics roles on LokerDollar pay around $115k/yr (range $9.7k–1000k/yr, n=187 active listings).

Hiring at Plata Card

Plata Card has 28 other active roles on LokerDollar and has been hiring here since Oct 13, 2026 — across Data & Analytics, Engineering.

View all Plata Card openings →

Market context

  • ESTIMATEEstimated pay is 39% below the role median of $115,000/year (n=187 pay-disclosing listings).
  • VERIFIEDPlata Card: 30 postings in the last 3 months, 30 all-time on LokerDollar.
  • VERIFIEDCompany first seen Oct 13, 2026.
  • VERIFIEDThis listing first seen Oct 13, 2026.
  • VERIFIEDLast verified live Oct 13, 2026.

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Remote-friendly · fits your timezone
Company
Plata Card
Estimated salary
$55k–85k/yr
Based on similar roles — not stated by the employer
Job Type
full time
Location
Remote · Open worldwide
Seniority
mid
PostedNew & verified
Sep 10, 2026

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Frequently asked questions

Is Data Scientist [Integrated Risk Management] at Plata Card a remote job?
Yes. Data Scientist [Integrated Risk Management] at Plata Card is a fully remote role open to candidates worldwide.
What type of employment is Data Scientist [Integrated Risk Management] at Plata Card?
This is a full time position.
How do I apply?
Click the "Apply" button on this page to go to the official application at Plata Card.

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