- Company Name
- Quince
- Job Title
- Senior Data Scientist, ML - Recommendations
- Job Description
-
Job Title: Senior Data Scientist, ML – Recommendations
Role Summary: Lead the design, development, and deployment of machine‑learning models that drive personalized search, ranking, and recommendation experiences across Quince’s site and app, collaborating closely with product, engineering, and business stakeholders to deliver data‑driven insights and continuous improvement.
Expectations:
- Deliver end‑to‑end ML solutions that improve personalization metrics (CTR, conversion, dwell time).
- Publish production‑ready models, run A/B experiments, and monitor performance with a focus on scalability and reliability.
- Translate analytical findings into actionable recommendations for non‑technical stakeholders.
- Foster a culture of data quality, reproducibility, and automated model lifecycle management.
Key Responsibilities:
1. Build and refine recommendation, ranking, and search models using supervised, unsupervised, and generative techniques.
2. Construct feature pipelines, evaluate feature importance, and optimize ranking algorithms.
3. Deploy models to production, orchestrate experiments, and establish monitoring dashboards.
4. Collaborate with product, engineering, and analytics teams to define data requirements and improve tracking infrastructure.
5. Communicate insights through reports, dashboards, and stakeholder meetings.
6. Champion automation of model development, testing, and deployment workflows.
7. Mentor junior data scientists and share best practices across the organization.
Required Skills:
- Advanced knowledge of statistical modeling, supervised and unsupervised learning, and recommendation system algorithms (e.g., collaborative filtering, neural CF, hybrid methods).
- Proficiency in Python (pandas, scikit‑learn, TensorFlow/PyTorch) and SQL; experience with data pipelines (Airflow, dbt, Spark).
- Expertise in ML experimentation frameworks (Optuna, Ray, SageMaker, or equivalent).
- Familiarity with BI tools (Looker, Tableau, Power BI) for data visualization and stakeholder reporting.
- Strong analytical reasoning, problem‑solving, and communication skills; ability to translate technical results to business impact.
- Experience with model monitoring, A/B testing, and continuous delivery in production environments.
Required Education & Certifications:
- MS or PhD in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative discipline.
- Minimum 2 years of industry experience as a data scientist in a consumer or e‑commerce setting.
- Relevant certifications (e.g., Google Cloud Professional Data Engineer, AWS Certified Machine Learning, TensorFlow Developer) are a plus.