Applied Data Scientist (Lead)

Amperity · Seattle WA

Company

Amperity

Location

Seattle WA

Type

Full Time

Job Description

Amperity is more than just a leading Customer Data Platform — it's a unique mix of people, technology, and opportunity. The people are whip-smart, deeply committed, and energizing. The technology is multi-patented, AI-powered, industry-shaping customer data management software that we invented because there was no way to solve the problems that we wanted to help consumer brands overcome. The opportunity is twofold: a market opportunity to provide a solution that consumer brands have been trying to find for decades, and a personal opportunity to grow and learn and hitch your career to a rocket ship.

Since our founding in 2016, Amperity has been growing 2.5X year-over-year. We've raised $187M in funding, including a recent Series D that increased our valuation to over one billion dollars. We're going places, fast, and we want you to come with us.

We help top brands make sense of massive amounts of transaction and engagement data so that they can finally know who their customers are, what opportunities exist, and how to provide the kinds of experiences that delight consumers and move the business metrics that matter. Our customers include Starbucks, Alaska Airlines, Patagonia, Kroger, J. Crew, Brooks Running, Planet Fitness, DICK's Sporting Goods, and many more.

We're building something that's never existed before, and we're doing it in a way that's great for consumers, transformational for our customers, and career-making for the members of the Amperity team. Come help us make it happen!

Interesting Problems

The Data Science team identifies, designs and implements algorithms that lie at the heart of Amperity's products. We focus on a few areas:

  • Identity matching: deduplicate and group billions of records to their underlying identities daily. Our customers use our predictions to create a personalized experience for their customers at every touchpoint.
  • Predictive scoring: With unified and enriched customer profiles (thanks to our entity matching algorithms), we build advanced customer-centric models to predict metrics/behaviors such as customer lifetime value, customer churn, product recommendations, and event propensity.
  • Causal Research: Causal inference helps marketers and analysts understand the impact and causality of marketing outreach. Our product should not only let them create campaigns and run experiments, but also learn the causal impacts of previous actions and provide optimization recommendations to achieve desirable outcomes more effectively in the future.

In addition to algorithmic development, we value sharing our findings with the broader data science community. We publish our research findings in top-tier peer-reviewed publications, engage with fellow data scientists by speaking at internal and external conferences, and also hold several patents focused on our core IP.

About You

We are looking for a versatile data science leader who can go deep to obtain useful insights for our customers (and help others learn to do the same). We are a team that moves quickly and relies on each other to think and work independently, handle ambiguity, and solve hard problems. If you are passionate about developing applied data science methodologies to help the world's most loved brands use their data to better serve their customers, and you are looking for an innovative, collaborative, and fun place to work, you should apply!

Qualifications:

  • Undergraduate degree in a quantitative discipline (e.g. statistics, mathematics, operations research, engineering, or computer science) with 5+ years of experience analyzing large data sets and building statistical/machine learning models in industry OR graduate degree in a quantitative discipline with 3+ years of similar experience
  • 3+ years of Machine Learning modeling or software development experience in a product company.
  • Familiarity with a broad set of supervised and unsupervised ML approaches and techniques, ranging from Regression to Deep Neural Networks.
  • Experience applying ML-based solutions to complex problems in business, science, or engineering.
  • Proficiency in model development, model validation and model implementation.
  • Fluency in more than one programming language such as Python, Scala, Java, etc.
  • Experience with common data science toolkits such as Scikit-Learn, Spark ML.
  • Proficiency in using query languages such as SQL.
  • Familiarity with data structures, algorithms, distributed computing (e.g. Spark, Map-Reduce, Presto), and cloud storage systems
  • Extensive knowledge in at least one of these areas: data integration and cleaning, entity matching, probabilistic databases, predictive analytics for marketing, or causal inference.
  • Experience building scalable machine learning pipelines
  • Experience with fast prototyping - quickly translating business problems into data modeling problems, collecting and analyzing datasets, and building ML prototypes before implementing in production.
  • Ability to synthesize complex ideas for both technical and non-technical audiences. Good communication skills in conducting code reviews, writing technical documentation, and giving internal and external presentations.
Benefits

We offer all the benefits you'd expect from a great place to work: 100% employee healthcare coverage, transportation subsidies, a comfortable work environment with plenty of snacks, and other employee experience perks like events, both in-person and remote. We also offer self-managed PTO and the flexibility to do your best work in the way that works for you. We provide an inclusive environment where you'll be challenged to find and unlock your full potential, surrounded by a team of world-class people driving for excellence.

Amperity is an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status.

Apply Now

Date Posted

09/04/2022

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