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# Data Scientist

- **Company:** HRCAP
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Salary:** $155,000.0 - $195,000.0
- **Contract:** Permanent contract
- **Skills:** Cloud Computing, Code Review, Data Integrity, Extract Transform Load (ETL), Data Warehousing, Distributed Computing Environment, Apache Hadoop, Python (Programming Language), Machine Learning, NumPy, Performance Tuning, Query Optimization, Backtesting, SQL Databases, Feature Store, Data Processing, Feature Engineering, Snowflake, Apache Spark, Deep Learning, Model Validation, Pandas, Information Technology, AWS Data Analytics, Software Library, Unsupervised Learning
- **Published:** October 7, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/ot4tzadbjd

## About the Role

* Education & Domain Expertise: Bachelor's or Master's degree in a highly quantitative field (Data Science, Statistics, Quantitative Finance, Mathematics, or Computer Science) alongside 3 to 5 years of professional experience engineering and deploying production-level predictive models within fintech or corporate banking.
 * Machine Learning & Statistical Mastery: Deep technical skill in supervised/unsupervised learning, time-series forecasting, and classification algorithms. Hands-on proficiency with machine learning libraries and deep learning frameworks.
 * Data Manipulation & Advanced Querying: Production-grade Python programming skills (highly proficient in Pandas, NumPy) for complex feature engineering, paired with expert-level SQL capability (mastery of window functions, CTEs, query optimization, and performance tuning).
 * Big Data & Cloud Infrastructure: Practical experience handling massive, concurrent transactional datasets using distributed computing frameworks (Spark, Hadoop) and modern cloud data warehouses (Snowflake, AWS data architecture).
 * Model Rigor & Code Validation: Methodical skill in model validation, back testing methodologies, and identifying/reducing statistical bias, combined with a strong track record of participating in rigorous, collaborative code reviews.
 * Global Collaboration & Languages: Bilingual proficiency in English and either Korean, Mandarin, or Japanese is highly preferred and will be heavily utilized given our deeply integrated global client portfolio.

## Description

* Predictive Modeling & Deployment: Design, train, and maintain scalable machine learning and statistical models to tackle complex financial challenges, including predictive credit scoring, risk assessment, and lifetime value modeling.
 * Anomaly Detection & Fraud Stewardship: Build and optimize algorithmic security layers to uncover transactional anomalies, flag fraudulent market activity, and ensure platform-wide data integrity.
 * Advanced Pipeline Optimization: Partner closely with Data Engineers to scale, maintain, and document underlying feature stores and automated ETL data pipelines, translating architectural constraints into algorithmic efficiencies.
 * Cross-Functional Strategy: Bridge the gap between quantitative metrics and financial products by delivering concise algorithmic insights to Product Managers, Risk Officers, and executive stakeholders to drive commercial decision-making.