Senior Data Science Lead (AI)

TL;DR

Senior Data Science Lead (AI/ML): Leading the design and implementation of complex data science solutions and advanced statistical models with an accent on scalable data pipelines and model optimization. Focus on automating model deployment, conducting rigorous hypothesis testing, and mentoring junior data scientists to drive strategic business impact.

Location: Hybrid in Tampa, Florida, United States

Company

hirify.global is a digital transformation company specializing in AI and data engineering services.

What you will do

• Lead the design and implementation of complex data science solutions to drive business impact and strategic decision-making.
• Develop, validate, and optimize advanced statistical and machine learning models, including regression, classification, and forecasting algorithms.
• Build scalable data pipelines and automate model deployment using tools such as KubeFlow and BentoML.
• Conduct rigorous statistical analysis, including hypothesis testing and probabilistic graph modeling, to uncover actionable insights.
• Mentor and guide junior data scientists, fostering a culture of technical excellence.
• Collaborate with cross-functional teams to translate business objectives into actionable analytics projects.

Requirements

• 12+ years of experience in data science, including hands-on expertise in advanced statistical modeling and machine learning.
• Expertise in hypothesis testing (T-Test, Z-Test) and advanced regression techniques (linear and logistic).
• Strong programming skills in Python, PySpark, and R.
• Proficiency with ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, Keras, or MXNet.
• Experience with forecasting techniques, including exponential smoothing, ARIMA, and ARIMAX.
• Hands-on knowledge of probabilistic graph models and classification algorithms (Decision Trees, SVM).

Nice to have

• Master’s or PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Experience with Great Expectation and Evidently AI for model validation and monitoring.
• Knowledge of advanced distance metrics such as Hamming, Euclidean, and Manhattan.
• Familiarity with MLOps best practices and CI/CD for data science.
• Relevant certifications in machine learning or analytics (e.g., TensorFlow, SAS).