Our Client is a marketing technology company that is reimagining how the worlds fastest growing retail brands transform casual shoppers into lifetime customers. Through their patented retail data model, they replace manual processes with an intelligent, AI driven workflow. They are credited with doubling email revenue, and increasing customer retention for more than 400 brands, including Express, Tommy Hilfiger, The North Face, Teleflora, and Bass Pro Shops. They have been recognized as one of the Best Places to Work by Glassdoor and ranked No. 241 on the Inc. 500 List, the most prestigious ranking of the nations fastest growing private companies.
They are looking for Principal Data Scientists with a strong mathematical background to work alongside their Engineering Teams to build the next generation of retail and commerce models that delight and empower marketers. The ideal candidate is one that has several years of experience researching, building, serving, and maintaining data science models at scale. They are able to work with their Product Team to translate product requirements into the correct objectives, perform literature searches to identify the right approach, design thoughtful experiments, and write production code to serve the model and maintain it. They have first hand experience with what works and what does not, and are eager to share this experience with both junior and senior members and guide them through that process. They are also able to, and excited to, help architect the data science infrastructure needed to accelerate innovation on models and facilitate serving and maintaining them. Finally, they should be curious and eager to identify and explore the myriad of other products that can be built on their unique data asset. Their culture emphasizes making good tradeoffs, working as a team, and leaving your ego at the door.
Over the past six years the company has shown that Marketing Teams can create meaningful and valuable experiences for their customers using only first party data, an increasingly important proposition with the rise in concerns around online privacy and third party data. As a Principal Data Scientist, you will be joining a dedicated group of Data Scientists and Engineers at the forefront of exploring exciting ways to activate that data asset. They build powerful models that enable Marketers to make the right decisions and engage their customers with personalized content that is timely, relevant, and valuable. Their approach to building models is an academic one, starting with a literature search, a baseline, and an iterative process of training and validation to identify the most suitable model that is as simple as possible and as powerful as necessary. They employ a wide variety of models, such as Bayesian models for predicting customer lifetime value, matrix factorization to identify a customers product affinity, and reinforcement learning models to optimize content, timing, and frequency of marketing communications.
Their models operate at scale and crunch through millions of data points to make decisions that have been shown to double revenue and triple reach, and are designed in a flexible manner to generalize across our set of 400plus diverse customers who span industries from apparel to automotive. To explore, build, deploy, and maintain models we leverage many tools such as BigQuery, Spark, Cloud SQL, Keras, TensorFlow, Airflow, Kubernetes, and Google Compute Engine. Finally, they are a team that values applied research and constantly exploring the frontier of what is possible, diving into fields such as topic modelling, restricted Boltzmann machines, recurrent neural networks, convolutional neural networks for image feature extraction, and differential privacy.
Identifying appropriate models, algorithms to solve product requirements
Meticulous experimentation to evaluate and compare models
Writing internal and external facing documentation describing models and approaches, such as wiki pages, white papers, blog posts or journal papers.
Deploying models to production and maintaining them
Evangelizing the company Data Science internally and externally
Identifying new opportunities to leverage our data asset
Proposing and drive technical initiatives
Proposing infrastructure to accelerate the pace of model exploration and improve model serving and maintenance
Being a technical mentor for senior and junior team members
Meeting with customers to discuss our machine learning models and roadmap
PhD or MS in a quantitative discipline such as Applied Math, Data Science, Physics, Statistics, or Engineering
Deep understanding of Statistical, Probabilistic Analysis and Linear Algebra
8 plus years of relevant industry experience, including internships
Experience building, delivering and maintaining Machine Learning and AI products
Experience setting ML, AI project roadmaps
Strong oral and written presentation skills
Experience in technic