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Remote Ai Math Trainer Jobs in Puerto Rico (NOW HIRING)

Julius 2 Grow

Work Type: Full-time, permanent Location: 100% Remote Reporting Line: International teams in the US ... Prepare datasets to support advanced analytics, including exploratory and explanatory AI/ML ...

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Data Analyst Pharmaceutical Industry

Julius 2 Grow

Remote

Full-time

Posted 4 days ago

Job description

Work Type: Full-time, permanent
Location: 100% Remote
Reporting Line: International teams in the US and Europe
Language Requirement: Advanced English (must-have)
Time Zone Preference: US East Coast

Role Overview

We are seeking a highly analytical and detail-oriented Data Analyst to support pharmaceutical brand, commercial (marketing), and analytics teams. This role plays a critical technical function by connecting healthcare data with media and marketing insights to drive clear, actionable business outcomes.

The ideal candidate is comfortable working with complex and imperfect data, applies strong statistical reasoning, and can translate sophisticated analyses into compelling insights for both technical and non-technical stakeholders. This is a fully remote role, collaborating closely with cross-functional teams across the US and Europe.

Key Responsibilities

  • Perform advanced SQL-based data transformations, integrating multiple internal and external data sources (e.g., claims, media, CRM, EHR-derived datasets).

  • Define, validate, and govern metrics aligned with pharmaceutical business needs (e.g., brand performance, HCP engagement, patient journeys).

  • Apply statistical analysis to identify trends, key drivers, and ensure analytical rigor in recommendations.

  • Maintain and evolve analytical datasets and workflows as new data is ingested.

  • Conduct in-depth exploratory data analysis (EDA) to uncover patterns, anomalies, and opportunities within complex healthcare datasets.

  • Translate analytical findings into clear, actionable insights tailored to stakeholders across marketing, analytics, strategy, and leadership teams.

  • Manually clean, normalize, and structure data to ensure quality and analytical readiness for deep-dive analyses.

  • Prepare datasets to support advanced analytics, including exploratory and explanatory AI/ML applications.

  • Develop dashboards and data visualizations that clearly communicate insights and support decision-making.

  • Collaborate cross-functionally with data science, technology, media, strategy, and client-facing teams.

  • Document methodologies, assumptions, and data limitations to ensure transparency and reproducibility.

Required Qualifications

  • Bachelors degree in Analytics, Statistics, Mathematics, Data Science, Economics, or a related field.

  • 24 years of experience defining and validating metrics within the pharmaceutical, healthcare, or life sciences industry.

  • Strong SQL proficiency, including complex joins, transformations, and performance optimization.

  • Experience working with cloud data warehouses (e.g., BigQuery).

  • Solid foundation in statistics and analytical reasoning (trend analysis, hypothesis testing, segmentation).

  • Proven experience with exploratory data analysis and large, complex datasets.

  • Ability to simplify complex data and insights for diverse audiences.

  • Experience with data visualization tools (Tableau, Power BI, Looker, or similar).

  • Strong collaboration skills and experience working with cross-functional teams.

  • Advanced English communication skills (required).

Preferred Qualifications

  • Experience with pharmaceutical commercial or media data (claims, prescriptions, CRM, hub, or media datasets).

  • Familiarity with AI/ML concepts and data preparation for modeling.

  • Experience using Python or R for analytics and data manipulation.

  • Understanding of pharma compliance, privacy, and data governance.

  • Previous experience working remotely with distributed, international teams across multiple time zones.

Key Competencies

  • Strong analytical rigor and attention to detail

  • Business-oriented problem-solving mindset

  • Clear, concise communication skills

  • Comfort working with ambiguity and imperfect data

  • Curiosity and continuous learning mentality

  • Team-oriented and collaborative approach