Über diese Entry Level Data Analyst Stelle bei Meds
Meds.com is a rapidly growing consumer technology firm operating a suite of healthcare businesses, including our flagship brand BlueChew. Our mission is to better patients' lives through innovative healthcare solutions. With a team of 350 professionals across various specialties, we've built scalable pharmacy, telemedicine, and e-commerce platforms using cutting-edge technology. As we continue our accelerated growth trajectory, we're launching new products to expand our patient base and accelerate growth. Join us in tackling exciting challenges at the intersection of healthcare and technology.
We are looking for a Data Analyst who thinks like a scientist. You won't just be building dashboards; you will be digging into the "why" behind our growth. You will help us optimize our subscription models, predict customer churn, and refine our marketing spend using both traditional SQL analysis and statistical modeling.
This is for recent grads or soon to be graduates only (Grad Dates : May 2026 – December 2026) who are looking to flex their Data Science muscles.
Join our team in Austin, TX - we're looking for someone who truly values and enjoys working in the office, not just tolerates it.
Responsibilities
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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).
What We’re Looking For
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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
Qualifications
Education:
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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:
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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.
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
