Senior Manager Machine Learning - Recommendations

Role Overview

You will drive the vision and strategy for Commerce Intelligence at Glance, focusing on Multi Modal Search, Recommendation Systems, Brand, and Price Affinity Modeling. This role is transformational in achieving the company's AI-first aspirations. The Commerce Intelligence team is critical for driving commerce across the platform.

Candidates should possess knowledge of current AI and machine learning capabilities and advancements, with a strong interest in the practical application of data science within recommendation and personalization technology. You will clearly articulate data science solutions to key stakeholders and customers, translating these into actionable business initiatives. The solutions provided will encompass product innovations, create efficiencies and automation, improve data and system architecture, mitigate business risks, and create process improvements.

We are seeking a leader who can articulate a vision and inspire a team to achieve it. This role requires someone who will remove obstacles, break barriers, empower, communicate, and engage, effectively harnessing advanced analytic data modeling systems to drive positive outcomes for customers. You will define strategy, oversee execution, and develop, collect, and report objective metrics to ensure success. Additionally, you will be responsible for driving employee engagement and increasing productivity across the Data Science and Engineering teams.

The Impact You'll Make

• Define the overall vision for our commerce intelligence, with a focus on enhancing 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 solutions, applying critical thinking to remove extraneous inputs.
• Conceive, plan, and prioritize data projects.
• Lead data mining and collection procedures, especially for 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, Economics, Analytics, or Data Science. A bachelor's degree 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.
• Comfortable using one or more distributed training technologies such as Apache Spark, RAPIDS, dask, etc., 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.
• Possess a high degree of curiosity and ability to rapidly learn new subjects.
• Experience in e-commerce is a plus.