- Company Name
- Flo Health Inc.
- Job Title
- Engineering Manager - Data Science Team
- Job Description
-
**Job Title:** Engineering Manager – Data Science Team
**Role Summary:**
Lead the Predictive Growth Optimization team by designing, deploying, and continuously improving production‑grade machine learning models that forecast user lifetime value and drive marketing spend decisions.
The role blends hands‑on modeling with technical leadership and cross‑functional collaboration, ensuring that predictive insights directly inform user acquisition, retention, and monetization strategies.
**Expectations:**
- Directly manage a multidisciplinary team of 4+ ML and backend engineers, responsible for hiring, mentoring, and setting technical direction.
- Own and evolve the core pLTV model architecture, integrating it into key business processes across growth, product, and finance.
- Build end‑to‑end production pipelines that enable millions of daily predictions, from MMM algorithms to real‑time forecasting tools.
- Translate business problems into actionable ML roadmaps and communicate complex concepts to executive stakeholders.
**Key Responsibilities:**
- Lead architecture design, implementation, and iterative improvement of predictive lifetime‑value models.
- Oversee end‑to‑end MLOps infrastructure: model versioning, monitoring, automated retraining, and compliance with data‑privacy regulations.
- Partner with Growth, Product, and Finance to align model outputs with strategic initiatives, such as user acquisition channels, retention campaigns, and budgeting.
- Maintain high testing coverage, A/B test design, and statistical validation to ensure model reliability and business impact.
- Mentor and cultivate a high‑performance team culture, enabling professional growth and technical excellence.
**Required Skills:**
- 7+ years of applied machine‑learning experience with live production deployments.
- 4+ years of managing technical teams (ML engineers or data scientists).
- Deep knowledge of supervised/unsupervised learning, time‑series analysis, and causal inference.
- Proficiency with PyTorch, TensorFlow, scikit‑learn, CatBoost or similar frameworks.
- Experience in growth analytics, attribution modeling, or marketing effectiveness.
- Proven ability to translate business metrics into data‑driven roadmaps.
- Strong MLOps background: model version control, monitoring, automated retraining, and cloud infrastructure (AWS/GCP/Azure).
- Solid foundation in data engineering: data pipelines, feature stores, SQL, and distributed processing.
- Excellent communication skills; able to explain technical models to non‑technical stakeholders.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related quantitative field.
- Relevant certifications (e.g., TensorFlow Practitioner, AWS Certified Machine Learning) are a plus but not mandatory.