- 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.
- PhD or Master's degree in Computer Science, Data Science, Statistics, or a related field.
- At least 4 years of relevant 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.
- Experience building Learning to Rank (LTR) models.
- Experience with real-time systems and large-scale data processing technologies like Spark, Hadoop, or Kafka.
- Customer and Partner-first
- Act with Urgency and Focus
- Integrity with our partners and data
- Accountability even when challenged
- Empowerment over hierarchy
- Growth over comfort
- 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
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Principal Applied Scientist - Menlo Park, United States - Cardlytics
Description
About CardlyticsRemember that time you got cash back on a cup of coffee through your banking app? That was us
Cardlytics (NASDAQ: CDLX) is the industry-leading purchase intelligence and incentives platform. We are a product-driven company that cares about three things: our people, our customers, and our partners. Together, we make commerce more rewarding for everyone by helping businesses attract, understand, and incentivize consumers through their banks' digital channels.
About the Team:
The Ads Marketplace team at Cardlytics comprises a dynamic group of scientists and engineers dedicated to rethinking and redefining ad delivery and optimization at scale. Our work directly impacts millions of customers daily, driving innovation and effectiveness in how advertising reaches its audience.
About the Position:
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.
Responsibilities:
Our shared values are the driving force behind everything we do. Across all roles, we are looking for teammates who embody these values:
At Cardlytics salary ranges are determined based on factors such as role, level, and location. Individual compensation may be determined by relevant skills, experience, education, training, and other role-specific criteria. This salary range will be narrowed during the interview process based on a number of the aforementioned factors.The base salary range provided below does not include bonuses and additional benefits.
The annual US base salary range for this role is:
$200,000-$255,000
Benefits and Perks
