Data Science Manager at Allergan Data Labs

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Data Science Manager Allergan Data Labs. . 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. Our iconic brands include BOTOX® Cosmetic, CoolSculpting®, JUVÉDERM® and more. The medical aesthetics business is ripe for rapid growth and disruption, and we are looking to add to our high performing team to do just that. . . 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 to add to our team as we prepare to launch a new array of game-changing technologies on our successfully adopted platform. If you’re interested in working within a startup-oriented environment, while having the backing of a very large company, please read on.. . As a . Data Science Manager. , you will report to the . Head of Data, . as well as continuously collaborate with key stakeholders across the business to solve the most important technical problems.. . Responsibilities. . . . Take ownership for achieving objectives and key results for your department, allocate resources, oversee & own technical solutions, and work with Data Technical Project Managers to communicate schedule, status, and milestones. . . . Manage a team of data scientists and analysts by setting goals, supervising work, evaluating performance, removing barriers, cultivating career development, and promoting job satisfaction. . . . In collaboration with Data Product Managers, work with cross-functional partners (Product Development, Marketing, Sales, Customer Success, etc.) to understand & document business requirements including objectives, estimated costs & benefits, inputs, accuracy, latency, scale, and governance constraints. . . . Make individual technical contributions, such as the following:. . . . Collaborate with Data Engineers, Software Engineers, and other business partners to identify, gather, cleanse, and organize data sets needed for analyses & modeling projects. . . . Perform exploratory data analyses using appropriate techniques (descriptive statistics, visual analytics, clustering, transformations, etc.) to understand, distill, and communicate the information content of data sets, and to extract features that are appropriate for formulation of metrics or as inputs to data models. . . . Conduct inferential, predictive, prescriptive, causal, and other statistical analyses including hypothesis testing & forecasting to answer business questions, improve customer engagement, and drive business growth. . . . Design, train, and evaluate machine learning and AI models while adhering to best practices including model selection, validation, bias/variance tuning, performance assessment, sensitivity analysis, dimensionality reduction, etc.. . . . Collaborate with Machine Learning Engineers to design and implement machine learning & AI models as scalable & robust solutions that can be deployed into production at scale, and help develop monitoring metrics to detect non-stationary behavior, anomalies, and degradation in production. . . . . . Enforce our governance & development standards, including processes & frameworks for logging experiments, code & model quality standards, documentation, and source controlling artifacts. . . . Review technical designs, code implementations, and results for their appropriateness, effectiveness, and adherence to standards. . . . Clearly document & present your work and informational materials at the appropriate level of detail to business partners & leadership. . . . Maintain sharp professional knowledge & skills, and stay abreast of new developments in data science, machine learning, & AI. . . . Generate intellectual property and business ideas that could generate value for the company, such as new use cases and approaches to using data. . . . Ability to work effectively from your remote location using modern collaborative tools running on a company-provided MacBook Pro. . . . Required Experience & Skills. . . . Completed BS, MS, or PhD in Computer Science, Mathematics, Statistics, Engineering, or other quantitative field. . . . At least 6 years of experience as a Data Scientist applying statistical methods and machine learning as an individual contributor to solve business problems. . . . At least one year of experience managing one or more teams of data scientists and analysts. . . . Experience designing, training, and evaluating machine learning models [Above-Intern: that have been deployed into production at scale]. . . . Strong programming skills in Python, an understanding of core computer science principles, and experience with Python data manipulation frameworks such as Pandas & . PySpark. . . . Strong data manipulation skills in SQL, and good understanding of relational database design. . . . Broad knowledge of basic computational statistics and good understanding of theoretical fundamentals of statistics. . . . Thorough and broad knowledge modeling and training techniques for machine learning & AI, as well as best practices for ensuring robustness and performance. . . . Experience with frameworks and libraries for machine learning & AI such as scikit-learn, HuggingFace, . PyTorch. , Tensorflow/Keras, MLlib, etc.. . . . Ability to apply statistical techniques for experiment design (e.g., A/B, multi-cell testing), causal inference methods, and time series analysis/forecasting. . . . Talent and skills for creating clear data visualizations for both technical & non-technical audiences. . . . Experience with data warehouses (e.g., dimensional modeling), data lakes/lakehouses, and other data architectures. . . . Familiarity with Data Engineering, DataOps, and . MLOps. principles and tools. . . . Strong interpersonal and verbal communication skills. . . . Ability to work effectively from your remote location using modern collaborative tools running on a company-provided MacBook Pro. . . . Preferred Experience & Skills. . . . Knowledge in domains such as recommender systems, fraud detection, personalization, and marketing science (e.g., attribution, customer LTV, propensity, uplift models). . . . Experience with deep learning architectures and frameworks (e.g., PyTorch, TensorFlow/Keras). . . . Familiarity with Large Language Models (LLMs), other generative AI modalities, and how they are applied in production. . . . Knowledge of vector databases, knowledge graphs, and other approaches for organizing & storing information. . . . MS or PhD in a relevant quantitative field. . . . Publications in data science, machine learning, AI, and/or other data-related topics . . . . . . Our Core Values . . . . 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. . . . . . . Perks . . . . 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 concerts, festivals 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 SkinMedica skin care products. . . . Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:. . . The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.. . We offer a comprehensive package of benefits including paid time off. (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.. . This job is eligible to participate in our short-term incentive programs.. . This job is eligible to participate in our long-term incentive programs.. . . Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law.Compensation Range (Minimum - Maximum)$125,500—$238,500 USD. . . . .