Lead Data Analyst - Remote

As a Lead Data Analyst at Facet, you will lead efforts to equip Facet operations and product teams with the insights they need to maximize performance. You will join the Data Science & Analytics team within Facet tasked with modeling, understanding, and automating various aspects of our growth, margin, and retention initiatives. You will work with your teammates and stakeholders on both displaying the truth of the past, while doing your best to predict the unknown. You should be comfortable with communication, analysis, information design, managing competing priorities, and writing quality code. In this role you will work with data across all domains of the business and support leaders from all departments. The perfect candidate loves working on a wide range of questions, has exemplary interpersonal skills, enjoys embedding themselves in cross-functional teams, and is creative in finding ways to solve ad hoc problems.

Day-To-Day Responsibilities:

• Create visibility of Facet operations and product performance: Measuring performance against assumptions is how we learn and improve. As Lead Data Analyst, it will be your responsibility to equip Facet teams with the data they need to see evaluate the performance of their processes and products.
• Drive improvement in Facet’s business: You will be responsible for analyzing data to discover ways to improve Facet’s business. You will proactively identify opportunities and prioritize your work to help Facet achieve its business priorities. You will work directly with your teammates across the business to educate them on insights and drive changes in their strategy.
• Be a trusted strategic partner: Data Science & Analytics supports all teams at Facet, meaning it’s critical that you build and maintain lines of communication with the teams that are driving metrics. You will embed yourself with these teams, build trust, learn their processes, and use your analytical skills to help them improve.
• Data Engineering: We are a newer team at a growing company, and you’ll need to do a lot of your own data engineering. Gather, clean, and preprocess data from various sources, ensuring accuracy and consistency. Collaborate with Analytics Engineering to ensure data workflows result in clean, optimized data models.
• Evaluate & Produce Quality: Good code is reviewed code. You will be involved in ensuring your and your teammates’ code is free from errors, bias, and is easy to understand.

Basic Qualifications:

• 6+ years of experience in a business intelligence, analytics, or decision scientist role, with at least 3 years of experience working directly with consumer data on marketing, sales, delivery of service, and retention problems
• Experience with BigQuery, Snowflake, or similar data warehouse solutions
• Proficiency with SQL
• Proficiency with dbt
• Proficiency with Google Sheets
• Proficiency with version control
• Proven ability to work both independently and as part of a team
• Experience collaborating with Analytics Engineers to create modular, highly optimized data models
• Experience collaborating with Data Scientists and Machine Learning Engineers to solve complex predictive problems
• An expert at building rapport and trust with business leaders and cross-functional teammates
• Proficient at investigating and documenting business processes and user flows
• Strong understanding of core consumer tech businesses and the metrics that matter to them, including: LTV, retention, CAC, RAC, ARR, ARPC, margin, NPS, CSAT, and behavioral metrics
• Experience working with data from Salesforce CRM
• Experience working with behavioral data from website and email tracking tools such as Google Analytics, Segment, and Iterable
• Familiar with best practices in secure data handling and customer data privacy

Preferred Qualifications:

• Prior experience in the financial planning industry
• Prior experience in the consumer technology industry
• Proficiency with Python
• Proficiency with Airflow
• Experience building reports in scriptable BI tools like Streamlit or Dash