Associate Risk Data Scientist (Remote - US) at Jobgether

, , United States -

Full Time

Start Date

Immediate

Expiry Date

08 Feb, 26

Salary

0.0

Posted On

10 Nov, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Analysis, Statistical Modeling, Python, SQL, Clustering, Classification, Regression, Neural Networks, Anomaly Detection, Problem-Solving, Communication, Risk Analysis, Financial Data Analysis, Experiment Design, Portfolio Analysis

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Associate Risk Data Scientist in United States. We are seeking a motivated and detail-oriented Associate Risk Data Scientist to join a growing team focused on safeguarding financial operations through innovative data-driven solutions. In this role, you will develop and deploy machine learning models, analyze credit portfolios, and help identify potential financial risks. You will collaborate with cross-functional teams to design experiments, evaluate model impact, and communicate insights to both technical and non-technical stakeholders. This position provides a unique opportunity to gain hands-on experience in risk modeling and financial data analysis while contributing to meaningful solutions that enhance trust and safety in financial systems. The ideal candidate is analytical, curious, and eager to grow in a fast-paced, innovative environment. Accountabilities: Develop, implement, and maintain machine learning models for fraud detection, transaction risk, and credit underwriting. Analyze and monitor credit portfolios to minimize financial losses. Design experiments and evaluate the impact of data science solutions on operational and business outcomes. Collaborate with stakeholders to identify process improvements and address pain points with sustainable solutions. Communicate complex analytical findings clearly to both technical teams and business partners. Proactively research, experiment, and contribute to new methodologies in risk and financial data analysis. Bachelor’s degree in a technical field such as Statistics, Computer Science, Economics, Mathematics, or the Physical Sciences. Experience with data analysis and statistical modeling using Python, SQL, or similar tools. Familiarity with a variety of machine learning techniques, including clustering, classification, regression, neural networks, and anomaly detection. Strong problem-solving skills with the ability to navigate ambiguity and deliver actionable insights. Excellent communication skills for presenting findings to diverse audiences. Preferred: experience applying data science to risk-related problems in financial or SaaS environments. Must have authorization to work in the United States without requiring visa sponsorship. Competitive base salary with eligibility for bonus and equity programs. Comprehensive medical, dental, and vision coverage (100% company-paid for employees). Flexible spending accounts (FSA) and Health Savings Accounts (HSA). Life insurance, long-term and short-term disability coverage. Paid holidays, wellness days, and flexible time off. Employee Stock Purchase Program with discounts. Wellness and fitness initiatives. Employee recognition and referral programs. Inclusive and collaborative work culture with growth and learning opportunities. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest! #LI-CL1

Responsibilities

Develop and deploy machine learning models for fraud detection and analyze credit portfolios to identify potential financial risks. Collaborate with cross-functional teams to design experiments and communicate insights effectively.