Engineering Manager (Data Science/ML)

Role Description and Mission:

The Data Science / ML Engineering Manager is a critical leadership role responsible for managing a team of Data Scientists ML Engineers and Software Engineers focused on architecting building and operating the next-generation Dispatch Optimization platform. This role demands deep expertise in Data Science Machine Learning constrained Optimization (Operations Research) and scalable cloud-native service development. 

You will drive scientific rigor and engineering excellence to transform model outputs into real-time high-impact dispatch decisions that directly optimize cost efficiency and service levels.

Key Outcomes:

Team Development & People Management

• Leadership & Mentorship: Directly manage and foster a small and high-impact squad of Data Scientists ML Engineers and Optimization Specialists providing expert technical guidance mentorship and day-to-day support.
• Talent Strategy: Attract develop and retain top talent in modeling ML engineering and cloud-native service development by cultivating a positive inclusive and collaborative high-performance team culture.
• Road-mapping & Project Management: Own the successful implementation and delivery of projects defined on the ML roadmap with the highest quality and on time. Define and implement robust Software Development Lifecycle (SDLC) processes tailored for ML and optimization (Agile/Scrum). Plan and manage platform feature development including project estimation risk management and resource allocation.

Strategic Technical Direction & Delivery

• Scientific Strategy: Lead the process to define and select the optimal Data Science Machine Learning and Optimization strategy. This includes facilitating deep technical discussions within the team reviewing and challenging proposed approaches and making the strategic decision that balances scientific rigor (as assessed by the team) technical feasibility and overall business impact.
• System Architecture & MLOps: Guide the design and implementation of end-to-end cloud-native Python services (batch/streaming) that execute constrained optimization algorithms and deliver low-latency real-time dispatch decisions.
• Operationalize: Define and foster the MLOps strategy ensuring the automation of model training validation A/B testing/rollout and production monitoring using tools like SageMaker Airflow or similar industry platforms.
• Technical Excellence: Actively manage technical debt and ensure the prompt resolution of critical production issues by maintaining robust monitoring alerting and logging systems. Collaborate with Architecture to guide platform design and identify opportunities to integrate emerging technology trends.

Communication & Operational Rigor

• Communication: Partner effectively with Product Operations and Data Engineering teams. Clearly communicate complex technical findings scientific trade-offs and operational risks to non-technical stakeholders and executive leadership.
• Continuous Improvement: Establish metrics for product performance (e.g. NPS / cost telemetry) monitor operational health identify failure modes and drive rapid iteration cycles based on empirical data.
• Operational Compliance: Maintain rigorous operational standards manage platform development and deployment costs and ensure security and regulatory compliance activities including external audits and system documentation

Skills Education and Experience:

EDUCATION:  Bachelor's Degree (Master's preferred) in Computer Science Computer Engineering Data Science Operations Research or a closely related quantitative field.

EXPERIENCE: 

• 6+ years relevant experience in Data Science ML Engineering or Operations Research with significant experience transitioning research models into production-grade scalable systems.
• 2+ years proven experience in engineering management or a similar technical leadership role specifically managing Data Science or ML Engineering teams.
• Demonstrated track record of successfully leading and shipping complex DS/ML and Optimization projects (e.g. dispatch platforms real-time decision engines) that delivered measurable business value.
• Experience managing and operating 24x7 real-time information systems and/or technical operations.

ROLE BASED COMPETENCIES (KNOWLEDGE SKILLS & ABILITIES): 

• Technical Expertise: Deep understanding of Data Science ML techniques (e.g. XGBoost PyTorch Transformers) optimization methods (MIP/Linear/Stochastic) and architectural requirements for low-latency real-time decision services. Skilled in Python SQL and Cloud (AWS) MLOps and Data pipelines (Airflow SageMaker or equivalents).

Leadership and Team Management: Proven ability to inspire lead mentor and hire specialized DS/ML talent fostering a collaborative data-driven environment.

• Project Management: Expertise in project estimation planning and risk management within an Agile/Scrum framework including defining and driving technical roadmaps.
• Communication: Exceptional ability to partner with cross-functional stakeholders (Product Ops) and present scientific and operational findings to executive audiences.

Innovation and Trend Awareness: Proactively identifies evaluates and champions emerging Machine Learning models and research paradigms (e.g. LLMs Generative AI Causal Inference Foundation Models) and assesses their direct potential to solve critical business problems or unlock new product capabilities.

WORKING RELATIONSHIPS:  Collaborates with cross-functional teams including engineering product management QA and operations. Communicates regularly with senior leadership and external stakeholders as needed.

ADDITIONAL REQUIREMENTS: Flexibility to adapt to changing priorities and fast-paced environments. Availability for occasional travel or extended hours as required for project deadlines production incidents and critical issues.

Hiring In:

• United States: Arizona California Florida Georgia Illinois Massachusetts Michigan New Hampshire New Mexico New York State North Carolina Tennessee Virginia Texas Colorado.

The anticipated closing date to submit applications for this role is May 25th. Join our Greenhouse Candidate Portal to track your application status and receive instant alerts for future openings.

What We Do

Agero is a leading provider of driver assistance accident management consumer affairs support and connected vehicle services for stakeholders across the automotive industry including the world’s largest automakers auto retailers insurers rideshare providers and other brands. As the driving force behind mobility support throughout all points in the vehicle ownership journey - from purchase to maintenance and breakdown to resell or trade in - we deliver a suite of powerful innovative services and technology solutions that enable our 100+ clients to provide their drivers with enhanced communication safety and convenience for whatever their vehicle need.

Why Work With Us

At Agero our solutions help drivers when they need it most. Our work directly impacts the lives of over 12 million people each year providing safety and peace of mind. We offer a unique career environment that combines the spirited energy of a fast-paced team with the stability of an established leader. Here you transform the road ahead and shap

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