Data Scientist

About the Company ZAGENO offers the largest life sciences lab supply marketplace. Our one-stop shop helps scientists, lab managers, and procurement leaders compare products, source alternatives, track deliveries, and communicate order statuses in real time. Leveraging advanced AI, ZAGENO enhances supply chain resilience and makes the customer experience superior, seamlessly integrating with existing systems to boost productivity and make online shopping for research materials convenient, efficient, and reliable. About the Role We are looking for a Data Scientist to build and maintain high-quality models that directly influence business decisions across pricing, shipping, conversion optimization, supplier intelligence, and operational automation. You will work closely with our Senior Data Scientist and cross-functional teams to turn well-defined analytical problems into production-ready solutions. This role is right for someone who is strong at modeling, cares about rigor, and wants to see their work drive real outcomes. What You’ll Do Modeling & Analysis Build predictive, optimization, and ranking models across key business domains including pricing, forecasting, and conversion Select appropriate modeling approaches by balancing performance, interpretability, and maintainability Conduct rigorous model evaluation using both technical metrics and business-relevant outcomes Iterate on models based on feedback from experiments and production performance Experimentation & Evaluation Support experiment design and analyze results to validate model effectiveness Monitor model performance and coverage in production Identify and flag degradation or drift proactively Scalable & Production-Ready Work Write clean, reusable code that can be productionized, not just prototyped Collaborate with Data Analysts and Engineers to deploy and maintain solutions Contribute to shared feature logic, data models, and analytical standards Cross-functional Collaboration Work with Senior Data Scientists, Product, and Engineering teams to understand requirements and deliver reliable solutions Communicate modeling decisions and trade-offs clearly to technical peers About You Required 2-5 years of experience in Data Science, Applied ML, or Advanced Analytics Strong proficiency in Python and ML libraries (scikit-learn, TensorFlow, or PyTorch) and SQL Hands-on experience with predictive modeling, experimentation, or optimization Solid understanding of statistics, model evaluation, and complexity vs. interpretability trade-offs Experience working with large datasets; familiarity with distributed computing tools like Spark is a plus Ability to write production-quality code and collaborate with engineering teams Preferred Experience in B2B marketplaces, eCommerce, pricing, supply chain, or operations analytics Experience with Databricks or large-scale data environments Exposure to ranking systems, forecasting, or recommendation systems Familiarity with ML deployment and monitoring in production environments What Success Looks Like Models are built rigorously, ship on time, and perform reliably in production You iterate quickly and improve model quality based on experiment results Your code and modeling work is reusable and raises the team’s overall capability You communicate trade-offs clearly and flag risks early