Data Analyst (Supply)

Join Shiftsmart, a company dedicated to managing partner supply and ensuring high-quality partners fill shifts for our customers. As a Data Analyst, you will build and maintain core data tables and models, investigate data anomalies, and support day-to-day operational decisions. You will collaborate with various teams and have the opportunity to develop predictive models. Ideal candidates have 2-4+ years of experience in analytics, data science, or a similar role, are comfortable with SQL and Python, and have strong problem-solving and communication skills.

• Construire et maintenir des tables de données et des modèles de base pour soutenir les décisions opérationnelles.
• Diagnostiquer les anomalies de données et les changements inattendus dans la performance commerciale.
• Collaborer avec les équipes interfonctionnelles pour comprendre les problèmes commerciaux et traduire les exigences en données.

• Analytically-minded: You have 2-4+ years of experience in analytics, data science, data engineering, quantitative operations, or a similar analytical role. You are highly comfortable with SQL and can work through complex queries. You are comfortable in Python (pandas, notebooks) for analysis and modeling, and you have experience working with DBT or are capable of quickly learning it. You enjoy getting into the details of a dataset and figuring out what is really happening
• High ownership: You are self-directed and don't wait for someone to tell you exactly what to do. You take a loosely defined problem, figure out what needs to happen, and drive it through to a solution
• Clear communicator: You can take a complex analysis or investigation and explain the key takeaway simply. You know how to communicate the "so what" to both technical and non-technical teammates
• Highly organized: You think in systems and process, relish bringing structure to ambiguity, ruthlessly prioritize, and feel organization is second nature to you
• Problem solver: You thrive working through and solving complex problems, you know how to turn an ambiguous question into a structured investigation and keep digging until you find the root cause