Job Description

Manager, Data Science

We are seeking a highly skilled and technically proficient Manager, Data Science to grow and support our data science team. This individual will be responsible for executing complex modeling efforts, building reliable data pipelines, and delivering high-impact analytical solutions that support business decisions. This role is ideal for a hands-on practitioner with strong expertise in machine learning, statistics, and data infrastructure who is ready to step into a team manager role.

Responsibilities

• Lead and mentor a small team of data scientists and ML engineers
• Partner cross-functionally with engineering, product, analytics, and business stakeholders to identify opportunities for data-driven innovation within an agile environment.
• Uncover deep insights from data and effectively connect them to user behaviors through compelling storytelling.
• Build, deploy, and validate machine learning models and algorithms for prediction, optimization, segmentation, and recommendation.
• Design and execute experimentation, statistical modeling, and A/B testing across products and initiatives.
• Ensure scalable deployment of ML solutions into production in collaboration with engineering teams.
• Define and uphold best practices in model development, versioning, monitoring, and reproducibility.
• Implement frameworks for model governance and performance tracking.
• Contribute to building a modern data science stack that supports experimentation, feature engineering, and model lifecycle management.
• Contribute to the development of robust data pipelines, feature stores, and model-serving architectures.
• Advocate for sound data management and partner with data engineering on upstream data quality and infrastructure needs.
• Stay abreast of emerging techniques in AI/ML and evaluate applicability to our business challenges.
• Cultivate a culture of curiosity, experimentation, and scientific rigor.

Qualifications

• 5–6+ years of hands-on experience in data science or machine learning roles, with some exposure to team collaboration or informal mentorship.
• Degree in Computer Science, Statistics, Mathematics, or a related technical field (MS/PhD preferred, or undergraduate degree with relevant work experience).
• Strong proficiency with Python, SQL, and modern ML libraries (e.g., scikit-learn, statsmodels, TensorFlow, PyTorch).
• Experience deploying ML solutions into production environments (e.g., via cloud platforms like AWS/GCP).
• Experience in digital product development, particularly with web or app platforms, demonstrating an ability to effectively contribute to the lifecycle of digital products.
• Strong understanding of experimental design, causal inference, and statistical testing.
• Exceptional communication skills with the ability to translate technical work into business impact.

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