Senior Applied Scientist (Ads) (Remote - United Kingdom)

Key Skills

Algorithms, matplotlib, NumPy, Optimization, Pandas, Python Programming, Scikit-learn, SciPy, Statistical modeling, XGBoost

Job Description

Yelp engineering culture is driven by ourvalues: we’re a cooperative team that values individual authenticity and encourages creative solutions to problems. All new engineers deploy working code their first week, and we strive to broaden individual impact with support from managers, mentors, and teams. At the end of the day, we’re all about helping our users, growing as engineers, and having fun in a collaborative environment.

Are you passionate about machine learning, statistics, and mathematical optimization models to make high-quality, high-impact automated decisions? Do you want to help local businesses grow and succeed? Yelp's Ads group works on challenging, multi-disciplinary problems at scale—spanning machine learning, data structures & algorithms, optimization, statistics, and distributed systems—with the goal of creating a healthy, valued marketplace between customers and advertisers.

As a Senior Applied Scientist within the Ads group, you’ll be joining a team that focuses on dynamically optimizing the allocation of ad campaign budgets across multiple channels.

This opportunity requires you to be located in the United Kingdom. We’d love to have you apply, even if you don’t feel you meet every single requirement in this posting. At Yelp, we’re looking for great people, not just those who simply check off all the boxes.

What you'll do:

• Translate ambiguous business requirements into mathematical problems and identify the appropriate modeling approach (machine learning, forecasting, mathematical optimization, reinforcement learning, etc.).
• Partner with the Product team to identify and scale business opportunities and shape the team's roadmap.
• Work closely with software engineers to build reliable, scalable, and maintainable solutions that embed algorithmic features that you and other applied scientists have prototyped.
• Work closely with data scientists to identify the appropriate strategy (simulation, A/B or MVT testing, geo experiments, etc.) to validate business outcomes.
• Manage and lead applied science projects independently.

What it takes to succeed:

• Proven track record of delivering value to organizations through modeling and developing algorithmic features.
• In-depth theoretical knowledge and extensive industry experience in traditional machine learning.
• Industry experience in mathematical optimization (mixed-integer linear programming, dynamic programming, etc.) in a relevant domain, such as online ads, pricing & revenue optimization, logistics optimization, control engineering, etc.
• Industry experience with large-scale experiments, preferably involving complex network effects.
• Expertise in Python, including pandas, Matplotlib, NumPy, SciPy, scikit-learn, XGBoost, and statsmodels.
• Sufficient software engineering skills to effectively work with software engineers.
• Ability to thrive in a fast-paced and high-impact environment.

What you'll get:

• Full responsibility for projects from day one, a collaborative team, and a dynamic work environment.
• Competitive salary, a pension scheme, and an optional employee stock purchase plan.
• 25 days paid holiday (rising to 29 with service), plus one floating holiday.
• £150 monthly reimbursement to help cover remote working expenses.
• £81 caregiver reimbursement to support dependent care for families.
• Private health insurance, including dental and vision.
• Flexible working hours and meeting-free Wednesdays.
• Regular 3-day Hackathons, bi-weekly learning groups, and productivity spending to support and encourage
• your career growth. 
• Opportunities to participate in digital events and conferences.
• £81 per month to use toward qualifying wellness expenses.
• Quarterly team offsites.