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IT​/Tech Associate, Data Analyst

Job in Seattle, King County, Washington, 98127, USA
Listing for: LatentView
Full Time position
Listed on 2026-06-05
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist, Machine Learning/ ML Engineer, Data Science Manager
Job Description & How to Apply Below
Designation:
Associate.

Level: L2

Experience:

5 to 8 years

Location:

Texas, Texas, United States.

Job Description

We are looking for an experienced and highly analytical Data Scientist to join our Risk Analytics team within the Merchant Cash Advance (MCA) and alternative lending domain. The ideal candidate should possess strong expertise in SQL, Python, Machine Learning, and statistical modeling, along with hands-on experience in risk analytics and financial data analysis.

The candidate will work closely with underwriting, risk, collections, fraud, and business teams to develop scalable predictive models and analytical solutions that improve portfolio performance, reduce risk exposure, and support data-driven decision-making across the MCA lifecycle.

This role requires a strong problem-solving mindset, deep analytical capability, and the ability to work with large and complex financial datasets in a fast-paced environment.

Key Responsibilities

Develop and deploy predictive models for MCA risk-related use cases including:

Default prediction Risk scoring Fraud detection Renewal propensity Delinquency forecasting & Collections optimization

Analyze merchant transaction data, repayment behavior, bank statements, and portfolio trends to identify business and risk insights.

Build and optimize complex SQL queries for large-scale data extraction, transformation, and analysis.

Design scalable data science workflows and analytical pipelines using Python.

Perform exploratory data analysis (EDA), feature engineering, model training, validation, and monitoring.

Collaborate with underwriting, credit risk, operations, and business stakeholders to translate business problems into analytical solutions.

Evaluate model performance using statistical and machine learning metrics and continuously improve model accuracy and stability.

Work with structured and semi-structured financial datasets from multiple internal and external data sources.

Support portfolio monitoring and early warning systems for risk mitigation.

Prepare dashboards, reports, and presentations for senior leadership and business stakeholders.

Ensure analytical solutions align with regulatory, compliance, and business requirements.

Required

Skills & Qualifications

Strong expertise in SQL including:
Complex joins,Window functions, Query optimization, Data aggregation, Analytical querying, Strong programming skills in Python.

Hands-on experience with Machine Learning algorithms and frameworks such as:

Scikit-learn, XGBoost, MLFlow

Strong understanding of:
Supervised and unsupervised learning Classification and regression techniques Statistical analysis Feature engineering Model evaluation methodologies

Experience with Python data libraries:
Pandas, Num Py, Matplotlib, Seaborn

Experience working with cloud and big data platforms such as AWS, Big Query and version control tool like Git

Domain Expertise

Strong experience in the Merchant Cash Advance (MCA), alternative lending, or financial risk analytics domain.

Good understanding of:
Merchant underwriting, Credit risk assessment, ACH/payment bbehaviour, Revenue-based financing, Fraud analytics, Portfolio risk monitoring, Collections and repayment lifecycle

Experience working with financial and transactional datasets.

Analytical & Soft Skills

Strong analytical thinking and quantitative problem-solving capability.

Ability to interpret complex business problems and convert them into scalable analytical solutions.

Excellent communication and stakeholder management skills.

Ability to work independently and collaboratively across global teams.

Strong attention to detail and data-driven decision-making mindset.

Preferred Qualifications

Experience in MCA, Fin Tech, or alternative lending organizations.

Exposure to MLOps, model deployment, or productionization workflows.

Experience with visualization tools such as:

Power BI, Tableau, Familiarity with risk strategy development and portfolio analytics.

Educational Qualification

Bachelor's or Master's degree in:
Computer Science / Data Science /Statistics/ Mathematics /Artificial Intelligence /Finance Analytics/ Engineering or related quantitative disciplines

Ideal Candidate Profile

We are looking for candidates who:

Have strong hands-on experience in data science and risk analytics,Possess deep analytical and problem-solving capabilities, Understand MCA or alternative lending business processes, And can deliver scalable, business-driven analytical solutions in a fast-paced environment.
Position Requirements
10+ Years work experience
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