Data Scientist (Client Analysis) (ML/AI)

Location: Remote in the USA with hybrid hubs in New York, Miami, San Francisco, Seattle, and Washington, DC

Base salary: $150,000–$185,000 per year, plus equity, benefits, and an annual bonus or commission plan.

Company

hirify.global builds identity trust infrastructure for the digital economy, verifying identities and preventing fraud for businesses, governments, and consumers.

What you will do

• Analyze massive customer datasets and produce actionable insights on model performance and risk management policies.
• Explain hirify.global products, algorithms, and analytical findings to technical and non-technical customer audiences.
• Create data stories demonstrating how identity fraud can be reduced and end-user experiences improved.
• Build analytical tools, automated workflows, reports, and reproducible data-quality processes.
• Partner with Sales, Solution Consultants, Account Managers, and Technical Account Managers to support customer growth and product optimization.
• Develop machine learning models when alternative approaches provide value beyond established production models.

Requirements

• Degree in a quantitative field or equivalent experience; an advanced degree is preferred.
• 2+ years of experience in data science, data analysis, or analytics engineering.
• Strong theoretical and practical knowledge of supervised and unsupervised machine learning.
• 2+ years of experience writing clean, performant Python and working with massive real-world datasets.
• Experience with SQL, relational databases, and cloud technologies such as AWS, Azure, Databricks, or GCP.
• Ability to communicate complex ML and AI models through presentations, dashboards, and interactive data stories.

Nice to have

• Experience in identity verification and fraud prevention.
• Experience with PySpark, Pandas, NumPy, H2O, SHAP, Seaborn, Jupyter, Redshift, Snowflake, S3, Databricks, Apache Spark, Airflow, Tableau, Looker, transformers, clustering, graph analytics, explainability, or LLM workflows.
• Knowledge of model monitoring, threshold tuning, backtesting, train/holdout/OOT analysis, API integrations, and automated validation testing.

Culture & Benefits

• Remote startup work environment with clear goals and individual accountability.
• Hybrid work options through hubs in five US cities.
• Base salary supplemented by equity, benefits, and an annual bonus or commission plan.
• Equal opportunity workplace with accommodation support during the hiring and onboarding process.