What’s so great about working on Calendly’s Engineering team?
We make things possible for our customers through innovation.
Why do we need you? Well, we are looking for a Head of Data Science & Machine Learning who will bring expertise around answering complex business questions with Data Science and operationalizing machine learning models with modern MLOps. You will report to the VP of Data & Infrastructure and will be responsible for leading Data Science / AI teams.
A day in the life of a Director of Data Science & MLE- Strategic Leadership: Develop and drive the Calendly’s AI and data science strategy, ensuring alignment with overall business objectives and market needs
- AI/ML Innovation: Lead the research, development, and deployment of advanced machine learning models, generative AI solutions to address complex business challenges and enhance product offerings
- Team Leadership and Development: Build, manage, and mentor a multidisciplinary team of data scientists, machine learning engineers, and researchers, fostering a culture of innovation, collaboration, and continuous learning
- Cross-Functional Collaboration: Work closely with Product, Engineering, Design, Marketing, Sales, and Customer Success teams to integrate AI/ML initiatives across the organization and ensure seamless execution
- Project Oversight: Oversee the end-to-end lifecycle of AI/ML projects, from ideation and prototyping to production deployment and monitoring, ensuring timely delivery and measurable business impact
- AI Governance and Ethics: Establish and enforce best practices for ethical AI development, data governance, compliance, and risk management, ensuring transparency, fairness, and regulatory adherence
- Stakeholder Engagement: Engage with internal and external stakeholders to understand business requirements, validate AI-driven solutions, and communicate technical concepts to non-technical audiences
- Continuous Improvement: Stay abreast of emerging AI/ML technologies and industry trends, driving innovation and process improvements within the team and organization
- Education: Advanced degree (Master’s or PhD preferred) in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field
Experience:
- 10+ years of experience in AI, machine learning, or data science, including significant leadership or management roles
- Proven track record of delivering complex AI/ML solutions at scale and driving measurable business outcomes
Technical Expertise:
- Deep knowledge of modern AI/ML algorithms, frameworks, and best practices (e.g., supervised/unsupervised learning, deep learning, NLP, computer vision)
- Strong programming skills in languages such as Python, R, or similar
- Experience with data engineering, analytics platforms, and cloud-based AI/ML infrastructure
- Leadership Skills: Demonstrated ability to build, lead, and mentor high-performing technical teams
- Strategic Thinking: Ability to develop and execute AI/ML strategies aligned with business goals and market demands
- Project Management: Strong project management skills, including resource allocation, timeline management, and budget oversight
- Communication: Excellent verbal and written communication skills, with the ability to influence and collaborate across all organizational levels and with external partners
- Ethics and Compliance: Commitment to ethical AI development, data privacy, and regulatory compliance
- Continuous Learning: Passion for staying current with AI/ML advancements and fostering a culture of ongoing professional development
This role is pivotal and leverages AI and data science as core drivers of innovation, efficiency, and competitive advantage.
What’s in it for you?Ready to make a serious impact? Millions of people already rely on Calendly’s products, and we’re still in the midst of our growth curve — it’s a fantastic time to join us. Everything you’ll work on here will accelerate your career to the next level. If you want to learn, grow, and do the best work of your life alongside the best people you’ve ever worked with, then we hope you’ll consider allowing Calendly to be a part of your professional journey.
Our Hiring Process:We aim to provide an inclusive and equitable candidate experience to everyone who expresses interest in working at Calendly. To learn more about our hiring process, please visit our careers page at www.careers.calendly.com.
Once selected for an opportunity, the recruiter assigned to the role will keep you informed every step of the way. Have questions? Let your recruiter know! Want to share your experience? We are passionately committed to improving and building on our process, and we consider feedback a gift.
If you are an individual with a disability and would like to request a reasonable accommodation as part of the application or recruiting process, please contact us at [email protected]. Calendly is registered as an employer in many, but not all, states. If you are located in Alaska, Alabama, Delaware, Hawaii, Idaho, Montana, North Dakota, South Dakota, Nebraska, Iowa, West Virginia, and Rhode Island, you will not be eligible for employment. Note that all individual roles will specify location eligibility.
All candidates can find our Candidate Privacy Statement here
Candidates residing in California may visit our Notice at Collection for California Candidates here: Notice at Collection
The ranges listed below are the expected annual base salary for this role, subject to change.
Calendly takes a number of factors into consideration when determining an employee’s starting salary, including relevant experience, relevant skills sets, interview performance, location/metropolitan area, and internal pay equity.
Base salary is just one component of Calendly’s total rewards package. All full-time (30 hours/week) employees are also eligible for our Quarterly Corporate Bonus program (or Sales incentive), equity awards, and competitive benefits.
Calendly uses the zip code of an employee’s remote work location, or the onsite building location if hybrid, to determine which metropolitan pay range we use. Current geographic zones are as follows:
- Tier 1: San Francisco, CA, San Jose, CA, New York City, NY
- Tier 2: Chicago, IL, Austin, TX, Denver, CO, Boston, MA, Washington D.C., Philadelphia, PA, Portland, OR, Seattle, WA, Miami, FL, and all other cities in CA.
- Tier 3: All other locations not in Tier 1 or Tier 2
