Data Analyst
Role details
Job location
Tech stack
Job description
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Advanced Analytics: Move beyond descriptive stats to conduct deep-dive analyses on customer behavior, LTV (Lifetime Value), and retention.
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Predictive Modeling: Build and maintain basic machine learning models (Regression, Random Forest, etc.) to forecast inventory needs and subscription health.
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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.
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Data Storytelling: Translate complex statistical findings into actionable "executive summaries" for our marketing and operations teams.
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Self-Service Tooling: Build and optimize Looker/Tableau dashboards that empower non-technical team members to answer their own data questions.
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Data Integrity: Partner with Data Engineering to ensure our "Source of Truth" remains accurate as we scale our data warehouse (Snowflake/BigQuery).
Requirements
Do you have experience in Supervised learning?, Do you have a Bachelor's degree?, * 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).
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The "Science" Bit: Strong grasp of statistics (probability distributions, hypothesis testing, and regression analysis).
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The "Analyst" Bit: Experience with BI tools like Tableau, Looker, or Sigma. You know how to make data look as good as it performs.
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Product Intuition: You don't just pull data; you understand the business levers of a subscription-based telemedicine company.
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Bonus Points: Experience with dbt (data build tool), Airflow, or specialized experience in the healthcare/pharmacy space.
Tech Stack:
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Data Warehouse: Snowflake / BigQuery
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Languages: SQL, Python (primary), R (secondary)
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Visualization: Tableau / Looker
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Transformation: dbt
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Environment: Dockerized development, Git-based version control
Education:
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Bachelor's degree in a quantitative field (Statistics, Data Analytics, Computer Science, Economics, or Mathematics). A Master's degree is preferred.
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3+ years of professional experience in data reporting, business intelligence, or marketing analytics.
Technical Requirements:
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SQL Mastery: You must be highly proficient in SQL for querying large datasets, joining complex tables, and data cleaning.
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Programming (Python/R): Proficiency in Python (Pandas, NumPy) or R for statistical analysis and automation is standard.
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Data Visualization: Experience with Tableau, Looker (LookML), or Power BI to create dashboards that tell a story to non-technical stakeholders.
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Excel: Advanced skills (Pivot Tables, Power Query, complex formulas) for quick ad-hoc analysis.
Data Science Expertise:
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Statistical Analysis: Understanding of A/B testing (experimentation), hypothesis testing, and regression models.
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Predictive Modeling: Ability to build basic models for Customer Lifetime Value (LTV), Churn Prediction, or Inventory Forecasting.
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Machine Learning Basics: Familiarity with supervised learning algorithms (like Random Forests or Logistic Regression).
Business & Domain Knowledge:
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Subscription Metrics: Deep understanding of SaaS/Subscription KPIs like MRR (Monthly Recurring Revenue), Churn Rate, and CAC (Customer Acquisition Cost).
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Marketing Analytics: Experience analyzing funnel conversion, attribution models, and digital ad performance (Google/Meta ads).
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Regulatory Awareness: Familiarity with HIPAA or general healthcare data security is a significant plus given their telemedicine nature.
Benefits & conditions
Pulled from the full job description
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Food provided
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Health insurance
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401(k) matching
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Paid time off
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Vision insurance
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Dental insurance
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Life insurance, Perks:
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100% company-paid Medical, Dental, Vision premium coverage, plus Short-Term Disability and Life Insurance.
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401K with company match.
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Paid time off and company-paid holidays
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Enjoy free daily lunch