Entry Level Data Analyst

Responsibilities

• Advanced Analytics: Move beyond descriptive stats to conduct deep-dive analyses on customer behavior, LTV (Lifetime Value), and retention. 

• Predictive Modeling: Build and maintain basic machine learning models (Regression, Random Forest, etc.) to forecast inventory needs and subscription health. 

• A/B Testing & Experimentation: Design and analyze rigorous experiments for our web platform and marketing funnels to ensure we are making data-driven product decisions. 

• Data Storytelling: Translate complex statistical findings into actionable "executive summaries" for our marketing and operations teams. 

• Self-Service Tooling: Build and optimize Looker/Tableau dashboards that empower non-technical team members to answer their own data questions. 

• Data Integrity: Partner with Data Engineering to ensure our "Source of Truth" remains accurate as we scale our data warehouse (Snowflake/BigQuery). 

What We’re Looking For 

• The Essentials: 3+ years of experience in a data-heavy role. You are a SQL expert and highly proficient in Python (specifically Pandas, Scikit-learn, and NumPy). 

• The "Science" Bit: Strong grasp of statistics (probability distributions, hypothesis testing, and regression analysis). 

• The "Analyst" Bit: Experience with BI tools like Tableau, Looker, or Sigma. You know how to make data look as good as it performs. 

• Product Intuition: You don't just pull data; you understand the business levers of a subscription-based telemedicine company. 

• Bonus Points: Experience with dbt (data build tool), Airflow, or specialized experience in the healthcare/pharmacy space. 

Tech Stack 

• Data Warehouse: Snowflake / BigQuery 

• Languages: SQL, Python (primary), R (secondary) 

• Visualization: Tableau / Looker 

• Transformation: dbt 

• Environment: Dockerized development, Git-based version control 

Qualifications

Education:

• Bachelor’s degree (or in progress) in a quantitative field (Statistics, Data Analytics, Computer Science, Economics, or Mathematics). A Master’s degree is preferred. 

Technical Requirements: 

• SQL Mastery: You must be highly proficient in SQL for querying large datasets, joining complex tables, and data cleaning. 

• Programming (Python/R): Proficiency in Python (Pandas, NumPy) or R for statistical analysis and automation is standard. 

• Data Visualization: Experience with Tableau, Looker (LookML), or Power BI to create dashboards that tell a story to non-technical stakeholders. 

• Excel: Advanced skills (Pivot Tables, Power Query, complex formulas) for quick ad-hoc analysis. 

Data Science Expertise: 

• Statistical Analysis: Understanding of A/B testing (experimentation), hypothesis testing, and regression models. 

• Predictive Modeling: Ability to build basic models for Customer Lifetime Value (LTV), Churn Prediction, or Inventory Forecasting. 

• Machine Learning Basics: Familiarity with supervised learning algorithms (like Random Forests or Logistic Regression). 

Business & Domain Knowledge: 

• Subscription Metrics: Deep understanding of SaaS/Subscription KPIs like MRR (Monthly Recurring Revenue), Churn Rate, and CAC (Customer Acquisition Cost). 

• Marketing Analytics: Experience analyzing funnel conversion, attribution models, and digital ad performance (Google/Meta ads). 

• Regulatory Awareness: Familiarity with HIPAA or general healthcare data security is a significant plus given their telemedicine nature. 

Perks

• 100% company-paid Medical, Dental, Vision premium coverage, plus Short-Term Disability and Life Insurance. 

• 401K with company match. 

• Paid time off and company-paid holidays  

• Enjoy free daily lunch