Data Analyst
$64K-$112K (Glassdoor est.)
About the Role:

The Data Analyst plays a critical role turning project requirements into actionable results. The ideal candidate for the position can do a complete life cycle data generation and outline critical information for each stakeholder. This person can analyze business procedures and recommend specific types of data, laying the foundation for predictive models. You'll be a collaborative, cross-functional partner with our Product, Marketing and Engineering teams uncovering insights, formulate and test ideas to accelerate our business.

Responsibilities:
Create factor analyses on customer lifecycle / funnel and conversion, with a focus on product analytics, ranging from onboarding journeys (path analysis) to activation / retention signals
Partner with data engineering to define requirements for data pipelines and warehouse (Snowflake, Athena) data models
Partnering with data science peers to identify gaps, improve quality, and share advanced modeling techniques and learnings.
Work with Product Management, and DevOps as needed to provide SaaS customer adoption/usage insight to be shared with sales, and marketing organizations
Perform extensive data validation/quality assurance analysis within large datasets
Diagnose data-related bugs and ensure they are resolved in a timely manner
Develop and maintain automated dashboards, metric reports and data visualizations (Looker, Mixpanel, Tableau) and train colleagues to use them
Support the business with ad hoc reporting
Develop a high level of expertise with Sauce Labs data by digging into the details, sources and history of the data
Requirements:
3+ years experience in data analysis in B2B companies specifically in Saas
BA or BS required
Experience using SQL, Python and R. Candidates should be equally strong exploring data through both SQL and BI tools.
Strong understanding of different database environments (Mongo, MySQL) including cloud-based ones (AWS)
Familiarity with data warehouse concepts and data models
Experience with modern visualization tools (Looker, Tableau) and/or other data analysis tools
Strong communication skills (both oral and written); Must be able to present results to senior leadership, internal and external stakeholders with the ability to translate between technical metrics and business KPIs.
Excellent organizational, motivational and interpersonal skills, capable of interfacing well at multiple levels within a large organization.
Outstanding analytic and modeling skills, proficient at conceptualizing, implementing, and evaluating highly accurate and scalable advanced analytics solutions to business problems.
Knowledge of health-related analytics concepts such as risk stratification, episode groupers, and benchmarks.
Professional and positive approach in building relationships and quickly gain credibility with senior executives.
A result and success-oriented mentality, conveying a sense of urgency and driving issues to closure while adapting and adjusting to multiple demands, shifting priorities, ambiguity, and rapid change
Sauce Labs
4.2
Sauce Labs
