Full-Time Head of Data Science

This is a role for a leader who thrives in a fast-moving product environment, where challenges fuel growth and every decision shapes the future.

With United Tech you will have the freedom to design, build, and re-engineer processes from the ground up, working side by side with a team that values initiative, knowledge sharing, and bold goals.

Your ideas will directly influence revenue, and you will see the tangible results of your work reflected in key financial metrics.

In this role, you will:

• Build, scale, and develop the Data Science team, including hiring, mentoring, and performance evaluation
• Define and execute a Data Science strategy aligned with business priorities
• Oversee the full lifecycle of DS projects from problem formulation to deploying models into production
• Prioritize initiatives based on business impact (ROI, time-to-market)
• Collaborate closely with product managers, analysts, engineers, and C-level executives

It’s all about you:

• Proven ability to implement best practices in Data Science: reproducibility, A/B testing, ML monitoring
• Strong track record in maintaining model quality (performance, drift, latency)
• Advanced Python skills (pandas, sklearn, numpy, xgboost; pytorch/tf is a plus)
• High-level SQL expertise (large datasets, query optimization)
• Hands-on experience with ML pipelines, orchestration (Airflow, Prefect), and monitoring (Evidently, MLflow, Prometheus)
• Experience with GCP
• Solid understanding of A/B testing, causal inference, and statistics
• Familiarity with architecture fundamentals (API, data pipelines, microservices — integration level)
• Cloud experience with AWS or Azure
• Knowledge of distributed computation tools (e.g., Spark, CloudRun)
• Proven track record with generative AI/NLP model deployment
• Experience in startups or high-growth companies
• Publications, conference speaking, achievements on Kaggle, or open-source contributions

Would be a plus:

• Experience optimizing company processes through AI solutions
• Implementation of AI tools across departments (development, support, marketing, etc.)

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