Junior Data Analyst

• Role: Junior Data Analyst
• Reports to: Senior Analyst or Analyst
• Location: New Delhi, India
• Contract: 24 months fixed term contract.
• Date update: Nov 2026

About CPI

CPI is an analysis and advisory organization with deep expertise in finance and policy. Our mission is to help governments, businesses, and financial institutions drive economic growth while addressing climate change.

With a team of experts across seven international offices, including a strong presence in emerging markets and developing economies, CPI is a leader in tracking sustainable investment trends, identifying innovative business models, and supporting the solutions that can drive the transition to a low-carbon, climate-resilient, inclusive economy. We are unique in our focus on finance, our ability to get the right people to the table, and our analytical rigor.

About the role

CPI’s data science team operates at the intersection of climate finance and advanced data analytics. We partner with climate finance analysts to develop rigorous methodologies to track climate finance trends and inform policy analysis, build repeatable data pipelines, and deploy cutting edge AI/ML techniques to ingest and analyze data. Much of the team’s work focuses on large, data-intensive projects to track climate finance flows at a global level and assess financial institutions’ transition to net zero, such as our widely recognized Global Landscape of Climate Finance and Net Zero Finance Tracker. However, data science team members contribute to quantitative analyses and scaling of analytical workflows across the organization.

CPI works at the cutting edge of climate finance and policy analysis, and this means that our data analysts must effectively combine technical rigor with a strong interest in the financial and policy questions that motivate our analytical work, and have the creativity and judgement needed to deal with ambiguity and incomplete/inconsistent data.

We are seeking a junior data analyst who is enthusiastic about developing their skills while contributing to CPI’s mission. The successful candidate will work on well-defined components of projects, with close mentorship from senior researchers and data analysts, and increasing responsibility over time.

Roles and Responsibilities

• Contribute to the development of quantitative methodologies and conduct exploratory data analysisunder the guidance of more senior colleagues, primarily supporting projects related to the tracking of climate finance flows and financial institutions’ net zero transitions. Help assess how structured and unstructured data sources can be used to produce analytical results.
• Develop and maintain robust data pipeline componentsthat ingest, clean, validate and process raw data according to defined standards, with code review and guidance from senior team members. Data sources will include structured datasets as well as unstructured/nontraditional sources. Our team works primarily in Python and PySpark, and manages data assets in Amazon Web Services.
• Support the application of AI/ML and statistical techniques to enhance data analysis, including ingestion of unstructured/nontraditional data; imputation of data where sources are incomplete; resolution of entities and transactions across inconsistent data sources; and classification of financial flows, commitments, and policies where labelled training data are scarce. You will apply these techniques under supervision while developing an understanding of their strengths and limitations.
• Assist research teams in querying, analysing, and interpreting data outputs, including by helping to build data dashboards and visualizations (sometimes in partnership with CPI’s Communications team). Contribute to narrative reports and presentations to disseminate analytical results.
• Support continuous improvement of the data science team’s best practices and data infrastructure, including by maintaining documentation and assisting with quality assurance processes.
• Effectively use AI assistants (primarily Codex) to enhance productivity, while critically evaluating their output.

Competencies and Experience

• A strong commitment to CPI’s mission and values.
• A university degree in a quantitative field, such as computer science, mathematics, statistics, engineering, economics, or finance. Candidates with degrees in other fields who can demonstrate strong data science/analytics skills will also be considered.
• Minimum of two years of professional experience in data science or analytics. Relevant internship, academic research, or capstone project experience will be considered.
• Demonstrated understanding of or interest in climate finance, public policy, financial institutions and markets, and/or international macroeconomics and finance.
• Proficiency in writing and understanding Python for data analysis and visualization and familiarity with SQL. Comparable experience and skills in another language, such as R, will also be considered when candidates are willing to translate those skills into Python.
• Foundational understanding of statistical and machine learning concepts. Relevant coursework or project experience might include econometrics, natural language processing, classification and clustering methods, or applied ML.
• Familiarity with Git/GitHub, or willingness to learn.

Personal Attributes

• Curiosity and eagerness to learn, including the ability to quickly acquire new technical skills and domain knowledge with guidance from colleagues. Strong communication skills, particularly in explaining quantitative analytics to non-technical audiences.
• Fluency in written and spoken English.
• Strong collaboration and organizational skills. Ability to manage assigned workloads, ask for help when needed, and incorporate feedback constructively.

Desired skills

• Experience using AI coding tools in production. We expect engineers at CPI to have a firm understanding of any AI generated code they deliver and the ability to critically evaluate their output
• Desirable: Experience using cloud platforms such as AWS, Azure, and/or Google Cloud Platform.
• Desirable: Exposure to financial datasets such as Bloomberg NEF, S&P Capital IQ, LSEG/Refinitiv, etc.
• Desirable: Familiarity with DataBricks

Position Details

• CPI is recruiting for one full-time position (40 hours) to be based in our India Office.
• CPI has adopted a flexible working policy whereby staff are able to mix working remotely with 3 days in the office.
• CPI offers an excellent and competitive compensation and benefits package.
• Applicants must be eligible to work in India, we are unfortunately unable to offer any visa sponsorship for this role.

To Apply

As part of your application please complete our application form by Monday 30th November, 2026

We do not recommend the use of AI to complete your application. We want to hear your own voice and reasoning in your application answers.

We encourage candidates to apply early, as we may close or pause this vacancy before the advertised deadline if we receive a high volume of applications.

Only short-listed applicants will be contacted.

Shortlisted candidates will be invited to complete a short technical exercise followed by one interview with data science and research staff.

Please be sure to add [email protected] to your contact list to ensure delivery of all correspondence from us.

Our Commitment

CPI’s mission is to create economic opportunity while protecting our environment. This worldview-grounding opportunity in something more fundamental that we all share and must protect-permeates our organization, and forms the foundation of our approach to Diversity, Equity, and Inclusion (DEI).

CPI’s approach to DEI mirrors our mission: within a culture that values transparency and dialogue, we strive to improve equity within our organization as well as in the communities in which we work. Internally and externally, we seek to remove inequitable barriers regardless of their origin, whether it be class, race, religion, nationality, region, political affiliation, gender, sexual orientation or physical ability. We are proactive in identifying and removing biases in our processes, seeking fairness in hiring, working conditions, and professional development.