Senior Manager Applied Science - Recommendations

About this role

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Skills you'll use

What you'll do

• Define the overall vision for our commerce intelligence, focused on up-levelling internal use of machine learning.
• Provide technical leadership of overall architecture, ML approaches, performance monitoring, continuing improvement, and production deployments.
• Manage, develop, coach, and mentor a team of machine learning engineers and big data specialists.
• Partner with our business and product teams to help predict system behaviour, establish metrics, identify bugs, and improve debugging skills.
• Ensure data quality and integrity within our products as well as our teams.
• Partner with our client-facing teams and customers to enhance products and develop client solutions applying critical thinking skills to remove extraneous inputs.
• Conceive, plan, and prioritize data projects.
• Lead data mining and collection procedures, especially focused on unstructured and siloed data sets.

Who can apply

• 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
• PhD or Master’s in a quantitative field such as Computer Science, Electrical Engineering, Statistics, Mathematics, Operations Research or Economics, Analytics, Data Science. Or bachelor's with additional experience.
• 10+ years of ML related industry experience working on large-scale recommendation systems or personalization. With 3+ years in a leadership role.
• You would bring deep expertise in the applied algorithms, models, and techniques used to design, scale, and optimize large-scale recommendation systems.
• You should be comfortable with software programming and statistical platforms such as Tensorflow, PyTorch, scikit-learn, etc. etc.
• You should be comfortable with 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

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