Senior Data Scientist, Yembo

• You leverage first principles to understand the art of the possible, and love solving customer pain points
• You're extremely hands on, technically excellent and exhibit strong communication skills
• You’re comfortable working directly with customers in order to best understand and implement workflows
• You love to troubleshoot issues
• Seeing your impact at scale excites you. You will have a direct impact on the overall company success
• You have a passion for making lives easier through automation and clever solutions
• 3-5+ years in a data-focused role, with demonstrable experience in both data engineering and data science
• Direct or related technical experience:
• Expert proficiency in SQL and relational database design
• Strong proficiency in Python for data manipulation (Pandas, NumPy) and scripting
• Hands-on experience building and maintaining ETL/ELT pipelines
• Experience with NoSQL databases, specifically MongoDB
• Experience with at least one major BI platform (Looker, Tableau, Power BI, etc.)
• Excellent communication skills; able to translate technical concepts to non-technical audiences
• Strong problem-solving ability and a self-starter attitude
• Pragmatic and results-oriented, with a focus on delivering business value
• Willing to work US business hours
• Occasional but infrequent travel

Desirable

• We're looking for an experienced Data Scientist to lead the transformation of our data from a raw storage asset into a strategic one.
• In this role you will be responsible for building a reliable data infrastructure, implementing a self-service business intelligence (BI) tool, and ultimately delivering the data-driven insights needed to accelerate our Product, Sales, and Customer Success efforts to develop features that continually push the limits of what Yembo's product can do
• To succeed in this role, you must be deeply technical, an analytical problem solver, and a strong communicator able to address technical problems in an effective way.
• By structuring our data and making it accessible, you will unlock critical insights, improve operational efficiency, and empower every team to make better, faster decisions
• First - Data Architecture & Pipeline Development (The Foundation)
• Design, build, and maintain a series of relational databases that sit on top of our MongoDB data lake
• Develop robust, automated, and scalable ETL/ELT pipelines to extract data from Mongo, transform it, and load it into the new relational databases
• Ensure data quality, integrity, and consistency, establishing a "single source of truth" for key business metrics
• Document the data models, schemas, and pipeline processes for company-wide understanding
• Second - BI Platform Enablement (Self-Service Analytics)
• Collaborate with the Engineering team to lead the evaluation, selection, and implementation of a modern BI tool (e.g., Looker, Tableau, Metabase). Looker is the current selection but that may change after a more indepth analysis
• Connect the BI tool to the newly created relational databases
• Build and maintain a core set of foundational dashboards and reports for company-wide use
• Train and empower business users across the company to self-serve their own data requests and create their own analyses
• Third - Data Science & Analysis (Actionable Insights)
• Act as the primary point of contact for data analysis requests from across the organization
• Support Product by analyzing feature adoption, user behavior, and the impact of product launches
• Support Customer Success by providing data and insights for customer-facing QBRs
• Support Sales and Marketing with data for lead scoring, market segmentation, and performance analysis
• Translate complex analytical findings into clear, actionable recommendations for business stakeholders