Role Overview
You will drive the vision and strategy for the Commerce Intelligence at Glance, specifically focusing on Multi Modal Search, Recommendation Systems, Brand and Price Affinity Modeling. This role is transformational in driving the company's AI-first aspirations. The Commerce Intelligence team is critical for driving commerce across the platform.
You should possess knowledge of current AI and machine learning capabilities and advances, with a strong focus on practical application within recommendation and personalization technology. You will clearly articulate data science solutions to key stakeholders and customers, translating them into actionable business outcomes such as product innovations, operational efficiencies, improved data and system architecture, business risk mitigation, and process improvements.
We are seeking an individual who can describe a vision and inspire a team to achieve it. You will be a leader who removes obstacles, empowers, communicates, and engages. Someone who truly harnesses advanced analytic data modeling systems to drive positive outcomes for our customers. From defining the strategy to execution, you will also develop, collect, and report objective metrics. You will own driving employee engagement and increasing productivity across the Data Science team and into Engineering.
The Impact You’ll Make
- Define the overall vision for our commerce intelligence, focusing on enhancing the internal use of machine learning.
- Provide technical leadership for overall architecture, ML approaches, performance monitoring, continuous improvement, and production deployments.
- Manage, develop, coach, and mentor a team of machine learning engineers and big data specialists.
- Partner with business and product teams to predict system behavior, establish metrics, identify bugs, and improve debugging skills.
- Ensure data quality and integrity within products and teams.
- Collaborate with client-facing teams and customers to enhance products and develop client solutions, applying critical thinking to remove extraneous inputs.
- Conceive, plan, and prioritize data projects.
- Lead data mining and collection procedures, especially focused on unstructured and siloed data sets.
- Experiment with new models and techniques.
- Drive the implementation of models into production through various Engineering teams.
- Create a positive culture to maximize productivity and minimize attrition.
The Experience You'll Need
- PhD or Master’s in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research or Economics, Analytics, Data Science. (Bachelor's with additional experience will also be considered).
- 10+ years of ML related industry experience working on large-scale recommendation systems or personalization, with 3+ years in a leadership role.
- Deep expertise in applied algorithms, models, and techniques used to design, scale, and optimize large-scale recommendation systems.
- Comfortable with software programming and statistical platforms such as Tensorflow, PyTorch, scikit-learn, etc.
- Proficient in using one or more distributed training technologies such as Apache Spark, RAPIDS, dask, along with MLOps stack such as kubeflow, mlflow, or their cloud counterparts.
- Comfortable collaborating with cross-functional teams.
- Excellent technical and business communication skills, with the ability to present technical ideas simply to business counterparts.
- High degree of curiosity and ability to rapidly learn new subjects.
- Experience in e-commerce is a plus.