Scale is at the forefront of enabling Machine Learning across multiple industries including self driving cars, financial services, government and global tech. As Scale’s Head of Central Operations, you’ll be leading the core central function that controls the key levers and metrics to balance supply and demand on our platform.
The role will involve leading a dedicated team and developing new products and solutions in order to advance our central models and controls. Candidates for the role will have experience in operations, product management, and technology. The ideal candidate will show a mix of the following traits: sophisticated understanding of supply and demand planning, demonstrated passion to work on tech/ops problems, strong entrepreneurial mindset and ability to drive “must win” outcomes.
The Central Operations Team is an interface between Growth and Customer Operations that will execute production priorities and handle day-to-day escalations and business judgments to improve operational productivity and efficiency.
This role will be accountable for reviewing planned touches per task and time per task, smoothing out need to root cause operational efficiencies. This allocation function will sync with new tooling and process in customer operations for concrete daily plans with explicit targets for hours, touches, and time per task. In executing allocations, the Central Operations head will also analyze and implement optimum policy for minimizing loss of productivity from queue and platform churn when moving taskers and retraining them between functional verticals.
You Will
- This role manages a central team that will own the end-to-end processes related to allocation of our taskers and workforces:
- True gate-keeping inspection of plans and assumptions in operations
- Mandating sound justification for additional headcount in operations
- Design and grow vertical cohorts of high skilled workers to enhance LT competitive advantage
- Ensure allocation efficiency by safeguarding vertical competencies with the introduction of concentric escalation levels
- Review final allocation matched initial mapping, with the introduction of Allocation SLAs
This role will also be critical for overseeing all aspects of our payment infrastructure:
- Payment operations specific to correction of pay errors and tactical approval review of bonuses to increase average tasks per active tasker or number of active taskers
- Day to day pay functions require central management to avoid competition of queues vs each other and to impose standards to avoid margin inflation when queue managers need a rapid response on hours inflation
- Assessment of analytical models for surge pricing will help inform central policy
- Removal of day-to-day escalations from the strategic development of pay structures and Growth will allow for investment of future programs and critical improvements.
Ideally you’d have:
- 10+ years of industry experience in an operational role and/or 3+ years in a top tier consulting or technology firm.
- 5+ years of direct managing experience.
- A degree in an analytics heavy major (e.g., Engineering, Physics, Economics or Mathematics) and/or equivalent work experience.
- Experience leading and influencing without authority.
- An entrepreneurial mindset that balances creative problem solving with the desire to run through walls to deliver outcomes.
- Polished verbal and written communication combined with the ability to understand internal and external stakeholder requirements and earn their trust.
- Strong intrinsic motivation to exceed goals and a bias for results.
- Analytical, planning, and process building capability.
Finally the role will be a critical for any internal and cross-functional work within and outside ops:
- Work closely with Ops leadership on the planning strategy to ensure successful support of
- Work with the rest of Operations to ensure supply / capacity planning and building are performed in alignment with demand forecasts, and to adopt / roll-out critical efficiency driving automation, processes, and best practices
- Work with Product & Engineering to identify changes to Scale’s systems / tools that reduce the occurrence & impact of bottlenecks affecting delivery scalability, and improve the efficiency & quality of the labeled data generated
Set the vision for the entire Central Ops organization, hire and mentor leaders to develop plans and goals, drive day-to-day execution, and create a powerful culture with operational excellence as its bedrock
About Us:
At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how machine learning can build innovative products. Our products provide access to human-powered data for hundreds of use cases and are used by industry leaders such as Open AI, Lyft, GM, Samsung, Airbnb, NVIDIA, and many more. We’ve recently raised $325 million in Series E funding at a valuation of $7B+ and are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.
What We Do
Scale accelerates the development of AI applications by helping computer vision teams generate high-quality ground truth data. Our advanced LiDAR, video, and image annotation APIs allow self-driving, drone, and robotics teams at companies like OpenAI, Lyft, Pinterest, and Airbnb focus on building differentiated models vs. labeling data.