Data Science - Manager / Lead

What are we looking for?

• Bachelor’s degree in analytics related area (Data Science, Computer Engineering, Computer Science, Information Systems, Engineering, or a related discipline)
• 7+ years of work experience in data science, analytics, engineering, or product management for a diverse range of projects
• Hands on experience with python, deploying ML models
• Hands on experience with time-wise tracking of model performance, and diagnosis of data/model drift
• Familiarity with Dataiku, or other data-science-enabling tools (Sagemaker, etc)
• Demonstrated familiarity with distributed computing frameworks (snowpark, pyspark)
• Experience working with various types of data (structured / unstructured)
• Deep understanding of all data science phases (eg. Data engineering, EDA, Machine Learning, MLOps, Serving)
• Highly self-motivated to deliver both independently and with strong team collaboration
• Ability to creatively take on new challenges and work outside comfort zone
• Strong English communication skills (written & verbal)

Roles & Responsibilities:

• Clearly articulates expectations, capabilities, and action plans; actively listens with others’ frame of reference in mind; appropriately shares information with team; favorably influences people without direct authority
• Clearly articulates scope and deliverables of projects; breaks complex initiatives into detailed component parts and sequences actions appropriately; develops action plans and monitors progress independently; designs success criteria and uses them to track outcomes; drives implementation of recommendations when appropriate, engages with stakeholders throughout to ensure buy-in
• Manages projects with and through others; shares responsibility and credit; develops self and others through teamwork; comfortable providing guidance and sharing expertise with others to help them develop their skills and perform at their best; helps others take appropriate risks; communicates frequently with team members earning respect and trust of the team
• Experience in translating business priorities and vision into product/platform thinking, set clear directives to a group of team members with diverse skillsets, while providing functional & technical guidance and SME support
• Demonstrated experience interfacing with internal and external teams to develop innovative data science solutions
• Strong business analysis, product design, and product management skills
• Ability to work in a collaborative environment - reviewing peers' code, contributing to problem- solving sessions, ability to communicate technical knowledge to a a variety of audience (such as management, brand teams, data engineering teams, etc.)
• Ability to articulate model performance to a non-technical crowd, and ability to select appropriate evaluation criteria to evaluate hidden confounders and biases within a model
• MLOps frameworks and their use in model tracking and deployment, and automating the model serving pipeline
• Work with all sizes of ML model from linear/logistic regression to other sklearn-like models, to deep learning
• Formulate training schema for unbiased model training e.g. K-fold cross-validation, leave-one- out cross-validation) for parameter searching and model tuning
• Ability to work on machine learning work like recommender systems, end-to-end ML lifecycle)
• Ability to manage ML on largely imbalanced training sets (<5% positive rate)
• Ability to articulate model performance to a non-technical crowd, and ability to select appropriate evaluation criteria to evaluate hidden confounders and biases within a model
• MLOps frameworks and their use in model tracking and deployment, and automating the model serving pipeline