
Staff Data Scientist
3 days ago
A successful candidate possesses deep expertise in Ad Tech, AI/ML, and Data Science, especially at scale. You should be comfortable with big data processing and cloud computing.
Skills & Expertise : You have a strong mathematical aptitude in areas like Statistics, Probability Theory, and Machine Learning. You're also proficient with data science languages and tools like Python or Apache Spark, which are essential for designing scalable solutions, implementing proof-of-concept models, and evaluating them both offline and online. A Curious Mind : Most importantly, you are passionate about investigating and learning from data, asking provocative questions, and are driven to build models that have a real business impact.
We value diverse academic backgrounds, so long as you demonstrate the intent to think and problem-solve like a data scientist. Our team includes engineers, mathematicians, computer scientists, physicists, economists, and social scientists—a great data scientist can come from any academic field.
A Master’s degree in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, or Economics. A Bachelor's degree from a reputable college with additional experience is also acceptable.
~7-10 years of work experience in a quantitative field, including experience in model building and validation.
~ Experience in the Ad Tech industry is a plus, where you would have applied machine learning and statistical techniques to solve real-world problems, particularly on large datasets.
~ Proficiency with software programming and statistical platforms like R or Python, including visualization tools.
~ Comfortable with the big data ecosystem and Apache Spark. Familiarity with Microsoft Azure, AWS, or Google Cloud/Vertex AI is a bonus.
~ Familiarity with the challenges of a world without identity data, especially for iOS and Android.
~ You will be responsible for leading one or more data science initiatives. This includes project ideation, solution design, measurement, iteration, coaching, deployment, and post-deployment management. Hands-On Work : This is a hands-on role where you will actively analyze data, design and develop models, and solve problems with the rest of the team.
Stakeholder Management : You'll be the interface between the data science team and internal stakeholders, including Product, Engineering, Data, and Business teams.
Model Building & Learning : You'll learn to identify business problems where AI can have the greatest impact, anchoring your model design in business context and end-user needs. You will gain experience in connecting model impact with measurable business results.
Our environment enables you to quickly build, launch, and review the performance of different approaches.
Creative Problem-Solving : Importantly, you’ll learn to be creative in your model design.
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