Climate Data Specialist - Analyst

MSCI Inc; Philippines; On-site; PHP 900,000 - 1,300,000; Full time

Job summary

MSCI Inc. is seeking a technically strong data professional to drive AI enablement and automation within the Climate Data and Content team. You will build tools, automate workflows, and apply Python, generative AI, and modern data practices to scale data operations.

You will own end-to-end data collection and QA, create dashboards, integrate LLM-based tools, and collaborate with analysts and stakeholders to ensure accurate climate and ESG insights across thousands of disclosures.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field.
• Experience in data operations, data engineering, or analytical roles; ESG/Climate exposure is a strong advantage; fresh grads welcome.
• Proficient in Python with at least 1 year hands-on scripting.
• Familiarity with SQL and BI tools (Power BI or Tableau).
• Strong analytical mindset, attention to detail, and excellent written and verbal communication.

Responsibilities

• Act as the team's internal AI champion — identify automation opportunities, prototype solutions, and drive adoption of AI tools across daily workflows
• Build and maintain Python scripts to automate repetitive data collection, transformation, QA, and reporting tasks
• Integrate LLM-based tools (e.g., Claude, Copilot, ChatGPT) into operational workflows for document extraction, content classification, and anomaly detection
• Design AI-friendly data collection methodologies that convert unstructured disclosures into structured, machine-readable formats at scale
• Validate AI-generated outputs, understand model limitations, and maintain human-in-the-loop accountability
• Own end-to-end data collection cycles — sourcing, processing, and validating climate and ESG data from company disclosures, vendor feeds, and public filings
• Design and implement multi-layer QA frameworks, rule-based checks, and anomaly detection logic to ensure data accuracy and consistency
• Develop and maintain operational dashboards, trackers, and reference systems to support SLA tracking and coverage monitoring
• Identify and resolve data integrity issues, coordinating with vendors, internal analysts, and technology teams as needed
• Identify opportunities to simplify, standardise, and scale existing workflows through tooling and automation
• Contribute to working groups and cross-functional projects aimed at expanding data coverage and operational capacity
• Train and support analysts in adopting new tools, scripts, and AI-assisted workflows
• Communicate clearly with internal and external stakeholders on data methodology, process changes, and query resolution

Skills

Python scripting

Data analysis

Communication

Analytical thinking

Stakeholder management

Education

Bachelor's degree in Computer Science

Bachelor's degree in Data Science

Bachelor's degree in Statistics

Tools

Power BI

Tableau

SQL

Job description

The Climate Data and Content team is responsible for research and assessment of carbon footprint and climate-related business initiatives for approximately 14,000 companies globally. We are evolving our operating model — shifting from manual, document-heavy workflows to intelligent, scalable, and auditable data processes powered by AI and automation.

This role sits at the heart of that transformation. We are looking for a technically strong data professional who can serve as an AI enabler within the team — someone who builds tools, automates workflows, and leverages Python, generative AI, and modern data operations practices in day-to-day work.

AI Enablement & Automation

• Act as the team's internal AI champion — identify automation opportunities, prototype solutions, and drive adoption of AI tools across daily workflows
• Build and maintain Python scripts to automate repetitive data collection, transformation, QA, and reporting tasks
• Integrate LLM-based tools (e.g., Claude, Copilot, ChatGPT) into operational workflows for document extraction, content classification, and anomaly detection
• Design AI-friendly data collection methodologies that convert unstructured disclosures into structured, machine-readable formats at scale
• Validate AI-generated outputs, understand model limitations, and maintain human-in-the-loop accountability

Data Operations & Quality Assurance

• Own end-to-end data collection cycles — sourcing, processing, and validating climate and ESG data from company disclosures, vendor feeds, and public filings
• Design and implement multi-layer QA frameworks, rule-based checks, and anomaly detection logic to ensure data accuracy and consistency
• Develop and maintain operational dashboards, trackers, and reference systems to support SLA tracking and coverage monitoring
• Identify and resolve data integrity issues, coordinating with vendors, internal analysts, and technology teams as needed

Process Improvement & Documentation

• Identify opportunities to simplify, standardise, and scale existing workflows through tooling and automation
• Contribute to working groups and cross-functional projects aimed at expanding data coverage and operational capacity

Stakeholder Collaboration

• Train and support analysts in adopting new tools, scripts, and AI-assisted workflows
• Communicate clearly with internal and external stakeholders on data methodology, process changes, and query resolution

Education

Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a quantitative field. Degrees in Finance, Environmental Science, or Sustainability considered with strong technical experience.

Experience

Experience in data operations, data engineering, or analytical roles; ESG/Climate exposure is a strong advantage. Fresh grads are welcome to apply.

Programming

Proficient in Python (minimum 1 years hands-on); able to independently script, automate, and analyze data pipelines

AI & GenAI

Active user of generative AI and LLM tools with demonstrated experience embedding them into operational workflows

Data & BI Tools

Working knowledge of SQL; experience with Power BI or Tableau desirable

Climate / ESG

Understanding of climate frameworks (TCFD, ISSB, GRI) and carbon reporting standards is advantageous but not required

Soft Skills

Strong analytical mindset, attention to detail, excellent written and verbal communication, and ability to manage competing priorities in a global, deadline-driven environment

Mindset

Proactive, curious, and eager to challenge the status quo — comfortable working at the intersection of data, technology, and sustainability