Data Scientist (AI)

Location: US GA ATL 201 STE 900

Company

hirify.global provides technology and financial services solutions, with a focus on fintech and the payments ecosystem.

What you will do

• Design, develop, validate, deploy, and monitor advanced analytics, machine learning, and AI solutions that produce measurable business outcomes.
• Perform exploratory analysis and prepare datasets from standard and novel data sources using data structures and algorithms.
• Apply predictive analytics, natural language processing, Generative AI, Agentic AI, and other emerging techniques to business problems across payments and financial services.
• Design experiments, hypothesis-testing frameworks, and statistical analyses for business strategies, product enhancements, and operational improvements.
• Establish best practices in data science, feature engineering, experimentation, model governance, and MLOps.
• Translate analytical results into actionable product recommendations and stay current with machine learning, AI, and financial services analytics trends.

Requirements

• Master's degree or higher in Mathematics, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative discipline.
• 1–3 years of experience developing and deploying end-to-end machine learning, predictive analytics, and data science solutions within the Payments, Banking, or Financial Services industry.
• Strong proficiency in Python and SQL.
• Hands-on experience with data wrangling, feature engineering, and model development using Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, or Plotly.
• Demonstrated experience building and deploying machine learning models in a production or near-production environment.
• Proficiency with data visualization and business intelligence tools such as Tableau or an equivalent.
• Strong analytical thinking and problem-solving skills, including the ability to translate ambiguous business problems into rigorous analytical frameworks.
• Ability to collaborate across product, engineering, and business teams.

Nice to have

• Experience within the Payments, Banking, or Financial Services industry.
• Experience with Databricks, including MLflow, Model Registry, collaborative notebooks, and MLOps workflows.
• Experience deploying cloud-native machine learning solutions, particularly in AWS environments.
• Familiarity with Transformer Models and Agentic AI technologies.
• Knowledge of model governance, regulatory compliance, and MLOps best practices in regulated financial services environments.
• Experience with big data technologies such as Spark or PySpark.

Culture & Benefits

• Collaborative, open, entrepreneurial, and inclusive work environment.
• Learning and development opportunities.
• Competitive salary and benefits.
• Opportunities to contribute to the future of fintech and give back.