Staff Data Scientist (Ad-Tech)

TL;DR

Staff Machine Learning Engineer (Ad-Tech): Leading the development of cutting-edge AI solutions within the mobile gaming and Ad-Tech industries, with an accent on designing, implementing, and optimizing complex machine learning models and recommendation systems. Focus on overseeing end-to-end data science projects, user personalization, dynamic pricing, and marketing attribution models.

Location: Hybrid model in Toronto & Montreal, Canada (2 days/week in-office)

Company

hirify.global is the #1 loyalty app for mobile gamers, helping them discover new games and earn rewards by playing.

What you will do

• Lead the design, implementation, and optimization of complex machine learning models and recommendation systems in the ad tech sector.
• Oversee end-to-end data science projects influencing user personalization, dynamic pricing, user segmentation, and marketing attribution models.
• Collaborate effectively with Product, Marketing, and Engineering teams to define, develop, and launch data-driven solutions.
• Create, scrutinize, and optimize predictive models, recommendation algorithms, and A/B testing frameworks.
• Mentor junior data scientists and oversee technical initiatives, fostering a collaborative data science environment.
• Contribute actively to hirify.global's data science thought leadership and represent the company externally.

Requirements

• 8+ years of experience in Data Science or Machine Learning, preferably in ad tech and advertising, with a strong focus on recommendation and recommender systems.
• Expertise in Python, advanced Machine Learning libraries (e.g., TensorFlow, PyTorch), SQL, and large-scale data processing.
• Experience with deploying machine learning models at scale in production environments and knowledge of MLOps practices.
• Experience in developing and deploying DNN algorithms in production.
• Strong grounding in statistics, hypothesis testing, and advanced analytics.
• Strong verbal and written communication skills to convey complex concepts and drive strategic discussions.

Nice to have

• Expertise in causal inference techniques and experience designing robust A/B testing methodologies.
• Track record of working on recommendation systems tailored for advertising and user engagement.
• Familiarity with the latest advancements in AI and machine learning within the ad tech industry.

Culture & Benefits

• Inviting and fun work environment with team lunches, game nights, and company-wide events.
• Culture deeply rooted in growth and upheld by smart, dynamic, and enthusiastic people.
• Utilize data to constantly learn, improve, and adapt.
• Foster an environment where everyone is encouraged to share ideas, push boundaries, take calculated risks, and witness visions come to life.

Hiring process

• AI tools may be used to support parts of the hiring process, such as reviewing applications or analyzing resumes.
• AI tools assist the recruitment team but do not replace human judgment.
• Final hiring decisions are ultimately made by humans.