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SalaryAt Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.
ABOUT THIS ROLE
As a Senior Data Scientist - Marketing Science, you will contribute across all aspects of paid media and brand measurement, bringing deep technical expertise in experimentation, causal inference, and statistical modeling. You will leverage your expertise to raise the bar on our scientific approaches. You will also effectively communicate with senior leaders about those scientific approaches in a way that builds consensus around our methodologies and measurement among both more- and less-technical audiences. Ultimately, you will help our business leverage science to make better decisions and increase the ROI of our marketing investments.
You will be the science lead for Audible’s scaled paid media experimentation program that leverages A/B tests to assess the incremental value of paid media investments. In this capacity, you will be accountable for the scientific soundness and integrity of our global paid media experiments at large scale. While you will not be expected to execute experiments yourself, you will collaborate with colleagues to ensure that test design and evaluation procedures meet a high scientific bar, including providing guidance to maximize the validity and reliability of our experiments. You will own formal meta-analytical work that evaluates the health of the program on an ongoing basis.
You will also be part of a cross-functional working team that develops and deploys marketing measurement models (e.g., marketing mix models, multi-touch attribution models, lifetime value models), and will be responsible for collaborating with economists, applied scientists, and other Data Scientists on the right model specification(s) to serve business needs in the context of paid media measurement. As an Amazon subsidiary, Audible scientists participate in the broader Amazon science community, and you will be part of a collaborative team that prepares Audible’s scientific approaches and models for central Amazon science review.
You will deliver and steward experimental measurement roadmaps in collaboration with our largest 3P media partners, including our paid media agencies and paid media platforms such as Meta and Google. You will innovate together with these partners on new forms of measurement that allow us to optimize our investments.
Finally, you will never lose sight of our core goal: enabling marketers to improve the ROI of Audible’s paid media and brand investments. You will work hand-in-hand with the business to translate complex scientific concepts into business-friendly communications, cultivating a partnership where you actively influence the strategic direction of our business through your scientific expertise.
ABOUT YOU
You have deep knowledge of statistics, causal inference, and experimentation. You are able to weigh trade offs in different types of designs for experiments and have a solid understanding of how to estimate the impacts of those trade offs on experimental power, noise, and bias. You have experience with different statistical modeling techniques for observational data (including both frequentist and bayesian approaches), and are familiar with model specifications that enable the estimation of causal effects (double machine learning or similar). You are comfortable with techniques that aid in the assessment of validity and reliability of both experiments and models, such as simulations, placebo testing, and A/A testing. While you may not have had exposure to specific marketing models in the past, you have experience applying your knowledge of statistics and modeling in different settings with different types of data. You are comfortable working with a team of cross-functional scientific peers from different disciplines (economics, applied science, engineering).
You have a strong ownership mindset. You are able to work with minimal instruction and oversight, conduct multiple tasks and projects simultaneously, and own deliverables end-to-end. You can effectively own a scientific roadmap, develop insightful analysis, and provide thoughtful input across a variety of scientific subjects. You have a knack for “seeing around corners” in an ambiguous and innovative environment, and you’re excited to develop your own solution when there is no ready-made playbook. You have an outstanding business acumen that helps you speak fluently in your business partners’ language, and helps them achieve or surpass their goals. You work fast and deliver reliably against your commitments.
As a Senior Data Scientist - Marketing Science, you will...
ABOUT AUDIBLE
Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. Our Hub+Home hybrid workplace model gives employees the flexibility between gathering in a common office space (work from hub) and remote work (work from home). For more information, please visit adbl.co/hybrid.
We are open to hiring candidates to work out of one of the following locations:
Newark, NJ, USA
Basic Qualifications
Preferred Qualifications
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
ABOUT THIS ROLE
As a Senior Data Scientist - Marketing Science, you will contribute across all aspects of paid media and brand measurement, bringing deep technical expertise in experimentation, causal inference, and statistical modeling. You will leverage your expertise to raise the bar on our scientific approaches. You will also effectively communicate with senior leaders about those scientific approaches in a way that builds consensus around our methodologies and measurement among both more- and less-technical audiences. Ultimately, you will help our business leverage science to make better decisions and increase the ROI of our marketing investments.
You will be the science lead for Audible’s scaled paid media experimentation program that leverages A/B tests to assess the incremental value of paid media investments. In this capacity, you will be accountable for the scientific soundness and integrity of our global paid media experiments at large scale. While you will not be expected to execute experiments yourself, you will collaborate with colleagues to ensure that test design and evaluation procedures meet a high scientific bar, including providing guidance to maximize the validity and reliability of our experiments. You will own formal meta-analytical work that evaluates the health of the program on an ongoing basis.
You will also be part of a cross-functional working team that develops and deploys marketing measurement models (e.g., marketing mix models, multi-touch attribution models, lifetime value models), and will be responsible for collaborating with economists, applied scientists, and other Data Scientists on the right model specification(s) to serve business needs in the context of paid media measurement. As an Amazon subsidiary, Audible scientists participate in the broader Amazon science community, and you will be part of a collaborative team that prepares Audible’s scientific approaches and models for central Amazon science review.
You will deliver and steward experimental measurement roadmaps in collaboration with our largest 3P media partners, including our paid media agencies and paid media platforms such as Meta and Google. You will innovate together with these partners on new forms of measurement that allow us to optimize our investments.
Finally, you will never lose sight of our core goal: enabling marketers to improve the ROI of Audible’s paid media and brand investments. You will work hand-in-hand with the business to translate complex scientific concepts into business-friendly communications, cultivating a partnership where you actively influence the strategic direction of our business through your scientific expertise.
ABOUT YOU
You have deep knowledge of statistics, causal inference, and experimentation. You are able to weigh trade offs in different types of designs for experiments and have a solid understanding of how to estimate the impacts of those trade offs on experimental power, noise, and bias. You have experience with different statistical modeling techniques for observational data (including both frequentist and bayesian approaches), and are familiar with model specifications that enable the estimation of causal effects (double machine learning or similar). You are comfortable with techniques that aid in the assessment of validity and reliability of both experiments and models, such as simulations, placebo testing, and A/A testing. While you may not have had exposure to specific marketing models in the past, you have experience applying your knowledge of statistics and modeling in different settings with different types of data. You are comfortable working with a team of cross-functional scientific peers from different disciplines (economics, applied science, engineering).
You have a strong ownership mindset. You are able to work with minimal instruction and oversight, conduct multiple tasks and projects simultaneously, and own deliverables end-to-end. You can effectively own a scientific roadmap, develop insightful analysis, and provide thoughtful input across a variety of scientific subjects. You have a knack for “seeing around corners” in an ambiguous and innovative environment, and you’re excited to develop your own solution when there is no ready-made playbook. You have an outstanding business acumen that helps you speak fluently in your business partners’ language, and helps them achieve or surpass their goals. You work fast and deliver reliably against your commitments.
As a Senior Data Scientist - Marketing Science, you will...
- Act as science lead for Audible’s scaled paid media experimentation program collaborating with colleagues to ensure that test design and evaluation procedures meet a high scientific bar, including providing guidance to maximize the validity and reliability of our experiments
- Own formal meta-analytical work that evaluates the health of our experimentation program on an ongoing basis
- Participate in cross-functional working teams that develop and deploy marketing measurement models, including collaborating with economists, applied scientists, and other Data Scientists on the right model specification(s) to serve business needs in the context of paid media measurement
- Deliver and steward experimental measurement roadmaps in collaboration with our largest 3P media partners, including our paid media agencies and paid media platforms such as Meta and Google
- Communicate clearly with senior audiences, translating complex scientific concepts into simplified, relevant outputs that can be quickly understood and actioned by both technical and non-technical colleagues
ABOUT AUDIBLE
Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. Our Hub+Home hybrid workplace model gives employees the flexibility between gathering in a common office space (work from hub) and remote work (work from home). For more information, please visit adbl.co/hybrid.
We are open to hiring candidates to work out of one of the following locations:
Newark, NJ, USA
Basic Qualifications
- Bachelor’s degree in relevant discipline and 8+ years of relevant professional experience OR Master’s degree in relevant discipline and 4+ years of relevant professional experience
- Experience in designing and evaluating experiments, including experience with formal meta-analytical approaches for evaluating programs of experimentation
- Experience with statistical modeling (both frequentist and bayesian approaches), including experience with articulating modeling trade-offs in a business setting
- Experience owning a science roadmap
- Deep expertise with Python and/or R
- Experience with SQL
Preferred Qualifications
- Doctorate in relevant discipline and 3+ years of relevant professional experience
- Experience in client-facing role, such as management consulting or marketing agency
- Professional experience working on and with production models (i.e. solutions that are scaleable and stable)
- Domain knowledge and expertise in Marketing Science, including (but not limited to) experience with marketing mix modeling (MMM) and experimental approaches typically used in assessing media ROI (e.g., user-based conversion lift models, geo hold-out tests)
- Experience in a similar business environment (entertainment industry, subscriptions businesses, digital commerce)
- Demonstrated success in communicating complex scientific concepts to less technical audiences, including business executives
- Exceptional writing and presentation skills
- High achievement in prior roles, with increasing levels of responsibility and independence
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
