Work Type: Full-time, permanent Location: 100% Remote Reporting Line: International teams in the US ... Familiarity with AI/ML concepts and data preparation for modeling. * Experience using Python or R ...
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Work Type: Full-time, permanent Location: 100% Remote Reporting Line: International teams in the US ... Familiarity with AI/ML concepts and data preparation for modeling. * Experience using Python or R ...
Linguist III
PR · Remote
US - NY - Remote Duration:8 months Job Title: Linguist lII (FAIR) Main duties: Perform linguistic ... Perform linguistic error analysis of AI model outputs, determining what the most frequent and ...
Linguist III
PR · Remote
US - NY - Remote Duration:8 months Job Title: Linguist lII (FAIR) Main duties: Perform linguistic ... Perform linguistic error analysis of AI model outputs, determining what the most frequent and ...
Remote Python Ai information
What are the key skills and qualifications needed to thrive as a Remote Python AI Developer, and why are they important?
To thrive as a Remote Python AI Developer, you need strong programming skills in Python, a solid understanding of machine learning concepts, and typically a degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (e.g., AWS, Azure), and relevant certifications such as TensorFlow Developer are highly valued. Exceptional problem-solving abilities, self-motivation, and effective remote communication skills help set professionals apart in this distributed role. These capabilities are critical for developing robust AI solutions, collaborating across virtual teams, and delivering impactful results in a rapidly evolving field.
What are Remote Python AI jobs?
Remote Python AI jobs are positions that involve developing, implementing, or maintaining artificial intelligence solutions using the Python programming language, all while working from a remote location. These roles can include tasks such as building machine learning models, automating data analysis, and deploying AI-powered applications. Professionals in these jobs collaborate with teams online, use cloud-based tools, and contribute to a variety of industries such as tech, finance, healthcare, and more. Python is a popular choice for AI due to its simplicity and the availability of powerful libraries like TensorFlow, PyTorch, and scikit-learn.
What is the difference between Remote Python Ai vs Data Scientist?
| Aspect | Remote Python Ai | Data Scientist |
|---|---|---|
| Required Credentials | Python programming, AI/ML knowledge, possibly certifications in AI or data analysis | Statistics, programming, data analysis, often a master's degree or higher |
| Work Environment | Remote, tech companies, AI-focused teams | Remote or on-site, diverse industries including tech, finance, healthcare |
| Employer & Industry Usage | Tech startups, AI firms, software companies | Various sectors like finance, healthcare, marketing, tech |
| Search & Comparison Intent | Focus on AI development using Python | Data analysis, insights, statistical modeling |
Remote Python Ai roles primarily focus on developing AI models and applications using Python, often within tech or AI companies. Data Scientists analyze data to extract insights, requiring broader statistical skills. While both roles may involve Python, Remote Python Ai emphasizes AI/ML development, whereas Data Scientists focus on data analysis and interpretation.
How is collaboration typically structured in a remote Python AI role, and what tools are commonly used to facilitate teamwork?
In a remote Python AI role, collaboration is often structured through regular virtual meetings, code reviews, and the use of collaborative platforms. Teams typically use version control systems like GitHub or GitLab for code sharing, and platforms such as Slack or Microsoft Teams for daily communication. Project management tools like Jira or Trello help organize tasks and track progress, while video calls via Zoom or Google Meet are used for team discussions and brainstorming sessions. This structure ensures that even in a distributed setting, team members can efficiently work together, share insights, and resolve challenges.
What are popular job titles related to Remote Python Ai jobs in Puerto Rico? For Remote Python Ai jobs in Puerto Rico, the most frequently searched job titles are:
What job categories do people searching Remote Python Ai jobs in Puerto Rico look for? The top searched job categories for Remote Python Ai jobs in Puerto Rico are:
What cities in Puerto Rico are hiring for Remote Python Ai jobs? Cities in Puerto Rico with the most Remote Python Ai job openings:
Full-time
Posted 14 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
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 ResponsibilitiesPerform 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.
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).
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.
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