As Head of Data at Caffeine, you will own the four pillars of our data practice: Data Backend Engineering, Data Engineering, Applied Data Science & Machine Learning, and Analytics. You will lead team members across these multiple domains and help multi-functional teams incorporate data into their backends services & event telemetry into clients. You will work with key business partners on understanding and charting our content and product strategy based on modeling of customer behavior and business metrics. You will design our ML algorithms that help surface the most relevant pieces of content to our users.

What You’ll Do:

• Design, build & extend our data platform and backend services to support a broad range of requirements and use cases across the organization.
• Lead our data infrastructure, working with vendors and platforms to support high reliability, robustness and performance.
• Develop team members through coaching the technical leads and engineers. You create structures for individuals to succeed together!
• Lead innovative approaches to content discovery within the Caffeine platform
• Leverage Data Science and other analytics skills to offer insights on features and product direction making.
• Work cross functionally with partners and products to integrate data driven decisioning into our organization.
• Spearhead work on Inference/ML/DL models to drive personalization product features and/or better digital user experiences.
• Build product features leveraging LLMs around content summarization, social content engagement and content discovery.

Who You Are & What You’ve Done:

• 10+ years of experience in a technical professional setting.
• Bachelor’s degree in computer science or similar applied technical field.
• You have led and developed a team of engineers at various stages of their careers.
• Object-oriented programming skills in a major language such as: Java, Scala, Python or Go.
• Experience working with SQL, MySQL, or similar analytics tools.
• Experience working on distributed systems in a real-time service layer.
• Experience with system design and data structures as well as ML / deep learning / statistical modeling.
• You prototype and implement insight-driven models.
• Demonstrated understanding working with real-time backend databases (such as NoSQL in-memory databases).
• Experience with generative AI large language models; embeddings and fine tuning. 
• Experience in one of the MPP big data platforms.

The starting base pay for this position is as shown below. The actual base pay is dependent upon multiple job-related factors such as professional background, work experience, skills, and market demand. These considerations can cause your base pay to vary. All full-time employees are also eligible for equity compensation and benefits.

The overall market range for this role is typically $205,000 - $223,000.