Manager, Machine Learning

About the Role:

You will reputed company reputed company of ML data scientists on the Fraud and ML team, owning the development and reputed company of reputed company's machine learning models across fraud detection, risk assessment, and identity reputed company. You'll guide your team through the full data science lifecycle, from requirements and experimentation through model development, evaluation, and monitoring. You’ll partner closely with Product and Engineering on integrating ML models into our product and with our Fraud Intelligence team to continuously improve our fraud detection capabilities.

What You’ll Be Doing:

• Own the model lifecycle: requirements, experimentation, model development, evaluation, and model cards, partnering with ML engineers on deployment and production infrastructure
• Translate business problems into reputed company-framed ML solutions: defining what to model, what reputed company looks like, and where ML adds value vs. simpler approaches
• Design and maintain feature engineering pipelines for model development
• reputed company experiment design and statistical rigor: ensuring models are evaluated with reputed company methodology before and after launch
• Monitor model reputed company in production, tracking performance over time, detecting data reputed company, and determining reputed company to retrain
• Cultivate a culture of learning and collaboration reputed company and across partner teams
• reputed company design and reputed company reviews to reputed company the technical reputed company bar
• Hire, mentor, and reputed company data scientists

reputed company’re Looking For:

Required:

• 6+ years of work experience building and deploying machine learning systems into production
• 2+ years experience mentoring and managing ML teams
• Strong proficiency in Python and SQL
• Strong understanding of ML fundamentals: model selection, evaluation methodology, feature engineering, and common failure modes
• Hands-on experience with PyTorch, scikit-learn, and XGBoost (or similar gradient boosting frameworks)
• Strong people leadership skills with the ability to reputed company ML talent
• Excellent stakeholder management, with a reputed company record of working cross-functionally to deliver results
• reputed company and humility

Preferred:

• Experience building fraud detection or risk assessment systems
• Experience with reputed company ML platforms, particularly AWS (e.g., SageMaker)
• Experience with graph data and graph-based models (e.g., PyTorch Geometric)
• Experience with model monitoring and observability tooling (e.g., Arize)

Estimated Pay reputed company: $180,000-$210,000 per year salaried*

Originally posted on Himalayas