Principal Applied Scientist

September 16

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Cardlytics

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2010

💳 Fintech

🤝 B2B

Description

• As an Applied Scientist in the Ads Marketplace team you will play a crucial role in developing sophisticated models that address key challenges in digital advertising • You will use advanced machine learning techniques to improve offer ranking, personalize user experiences, and predict user behaviors, such as clicks and conversions, thereby enhancing targeting accuracy and increasing advertising ROI • Develop and refine machine learning models for ranking, personalization, click and conversion prediction • Analyze large datasets to identify trends and insights that can be leveraged to improve model performance and advertising outcomes • Collaborate with engineering teams to integrate models into our production systems and ensure they scale effectively • Conduct A/B testing and other statistical analyses to validate model effectiveness and business impact • Continuously monitor model performance and make adjustments as market conditions change • Collaborate with cross-functional teams to understand business needs and deliver comprehensive data-driven solutions • Mentor junior scientists and contribute to the team’s knowledge base by staying current with industry trends and advancements in machine learning and data science

Requirements

• PhD or Master’s degree in Computer Science, Data Science, Statistics, or a related field • Experience in developing machine learning models for digital advertising • Proficiency in statistical programming languages such as Python, R, or Scala and experience with ML frameworks like TensorFlow or PyTorch • Strong problem-solving skills and the ability to work in a dynamic and fast-paced environment • Excellent communication skills, with the ability to translate complex technical details into clear business insights • Demonstrated expertise in predictive modeling techniques and their application to digital advertising problems (preferred) • Experience building Learning to Rank (LTR) models (preferred) • Experience with real-time systems and large-scale data processing technologies like Spark, Hadoop, or Kafka (preferred)

Benefits

• Flexible paid time off plus company holidays • Medical, dental, and vision insurance begins on your first day • 401(k) retirement plan with company match, plan also includes a student loan debt repayment option • Employee Stock Purchase Plan • Educational assistance for continuing education • Lifestyle Spending Account for physical, emotional, and financial wellness (like gym memberships, home down payments, art classes, park passes, and more!) • Complementary Calm app subscriptions to support employee mental health and wellbeing