Lead Data Scientist – Personalization
Allergan Data Labs is on a mission to transform the Allergan Aesthetics beauty business at Abbvie, one of the largest pharmaceutical companies in the world. Allergan Aesthetics brands include Botox, CoolSculpting, Juvéderm and many more. The medical aesthetics business is ripe for disruption and we're building a high performing Data Science and Engineering team to do just that.
Our leadership has a fresh and innovative vision for how the company should approach digital marketing and product. We are utilizing machine learning in an effort to intelligently engage our customers in a more personalized and effective way. Our team has successfully launched a new and innovative technology platform, Allē, which serves millions of consumers, tens of thousands of aesthetics providers and thousands of colleagues throughout the US. Since its launch in November 2020, Allē has delivered curated promotions, personalized experiences and had millions of consumers use it as part of their beauty journey
We're looking for an accomplished Lead Data Scientist who is interested in working within a vibrant startup-oriented environment while having the backing of a large company. If that's you, please read on.
The Lead Data Scientist will be responsible for partnering with Product, Engineering and Marketing teams to build a state of the art recommendation system and content personalization engine to maximize customer lifetime value.
As a Lead Data Scientist, you will:
- Design, train and apply statistics, mathematical models, and machine learning techniques to create scalable solutions for predictive learning, forecasting and optimization to drive business growth and members' engagement
- Build production ready recommendation engines to drive effective marketing and customer engagement via personalization.
- Create state-of-the-art fraud detection models
- Design experiments to study customer behavior and engagement patterns
- Own the full lifecycle of model development from ideation and data exploration, algorithm design and testing, algorithm development and deployment, to algorithm monitoring and tuning in production.
- Innovate with new approaches, staying abreast of current research in the recommendations field and the broader machine-learning community
- Share your technical solutions and product ideas with the team through robust documentations and effective presentations
- Participate in agile/scrum processes
Required Experience & Technical Skills:
- M.S. or Ph.D. (preferred) in Computer Science, Mathematics, Statistics, Operations Research or other quantitative field
- 4 - 6+ years of experience building, evaluating and deploying machine learning models at scale with expertise in one of the following domains – Recommendation systems, Fraud Detection, personalization, Marketing Science (Attribution, Customer LTV, Propensity, uplift models)
- Experience in using advanced statistical techniques for experiment design (A/B and multi-cell testing) and causal inference methods for understanding business impact.
- 4 -6+ years of experience with one or more of the programming language s such as Python, Scala, PySpark
- Experience with SQL, accessing and organizing data drawn from relational database
- Practical experience in deep learning architectures and frameworks is a plus
- Experience with computational statistics and understanding of theoretical fundamentals of statistics
- Strong knowledge of Linux-based OS and cloud platforms (AWS, Azure)
Additional Desired Competencies:
- Prior experience of building recommender systems at scale
- Experience with distributed systems such as Hadoop/MapReduce, Spark, streaming data processing, cloud architecture
- Have multiple public papers in the ML/AI areas
- Previous domain knowledge in digital marketing
- Be Humble: You're smart yet always interested in learning from others.
- Work Transparently: You always deal in an honest, direct and transparent way.
- Take Ownership: You embrace responsibility and find joy in having the answers.
- Learn More: Through blog posts, newsletters, podcasts, video tutorials and meetups you regularly self educate and improve your skill set.
- Show Gratitude: You show appreciation and return kindness to those you work with.
- Competitive salary.
- Competitive annual bonus targets.
- *401k with dollar for dollar match, up to 6% of eligible earnings (base, bonus). Plus additional company contribution.
- RSU grants (Long Term Incentives) for approved roles.
- Comprehensive medical, dental, vision and life insurance.
- *17 paid holidays per year, including 3 floating holidays.
- *Annual Paid Time Off (PTO), with separate sick days
- *12 weeks paid Parental Leave
- *Caregiver Leave
- *Adoption and Surrogacy Assistance Plan
- Flexible workplace accommodations.
- Free gym membership for those in our Irvine, CA WeWork office.
- We celebrate our wins with opportunities to attend Lakers, Knicks, Anaheim Ducks, Anaheim Angels and NY Rangers games.
- Opportunities to attend concert, festival and other live entertainment events in recognition of delivering great work.
- Attend AWS Re:Invent in person (Las Vegas) or virtually each year.
- Tuition reimbursement.
- Attend a tech or marketing conference of your choice each year.
- A MacBook Pro and accompanying hardware to do great work.
- A modern productivity toolset to get work done: Slack, Miro, Loom, Lucid, Google Docs, Atlassian and more.
- Generous discounts on Skin Medica skin care products.
- Discounted aesthetic treatment days multiple times a year.
- $600 worth of Alle benefits each year to use towards aesthetic treatments and products.
- Eligible for donation matching to over 1.5 million nonprofit organizations.
*New 2022 benefit
The Allergan Data Labs team is led and comprised of technology and marketing experts with experience ranging from successful tech startups to large medical corporations. Please don't be shy, we'd love to have you come by for a chat in our Irvine, CA offices if this opportunity piques your interest.
Significant Work Activities: Continuous sitting for prolonged periods (more than 2 consecutive hours in an 8 hour day)
Job Type: Experienced