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Climate Analytics and Alignment (C2A) – Data Scientist

BNP Paribas • France • Added on Oct 30, 2026
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This data scientist will build and improve analytical methods for assessing how BNP Paribas’s lending portfolios align with sector climate pathways. The work combines Python-based modelling, simulation tools and an internal dashboard, with analysis spanning high-emitting sectors such as energy, transport, steel and real estate.

The results can help the bank understand where its financing sits against climate objectives and support decisions about how client portfolios may transition toward net zero by 2050. The role connects data analysis with sector expertise and banking strategy, making the quality of assumptions and missing-data treatment relevant to the credibility of portfolio-level climate assessments.

This suits someone with a strong data science or analytics background, confident Python skills and interest in applying quantitative methods to climate transition and sustainable finance. Clear communication in French and English will matter when working with data specialists, sector experts and banking teams.

Job FAQs

What are the main missions and responsibilities of this role?

The role focuses on measuring credit portfolio alignment with climate pathways. The data scientist prepares sector analyses, develops and documents methodologies, adapts simulation programmes, models missing data and helps industrialise the GoNetZero project. They also contribute to an internal dashboard and work with sector specialists to test portfolio impacts, refine indicators and support the rollout of commercial strategies across emissions-intensive sectors.

Key learning opportunities for this job

The position could build expertise in climate-alignment methodologies, sustainable finance and the use of portfolio data to assess transition pathways. Working across sectors such as oil and gas, power, automotive, real estate and aviation may broaden understanding of how climate metrics differ by industry. The role also offers practical development in Python analytics, simulation, data industrialisation and dashboard design, alongside exposure to banking strategy and collaboration with climate and sector specialists. The posting mentions no specific certification or formal training programme.

How does the ideal candidate look like (experience, skills)?

The posting asks for a master’s-level qualification in engineering, university studies or an equivalent field, plus at least three years of data science or data analytics experience. Strong Python programming and analytical skills are central; prior climate experience is an advantage rather than a stated requirement. The work also calls for clear written and spoken communication in French and English, initiative and a collaborative approach. Experience with modelling, incomplete datasets or analytical tools would be relevant to the described methods and simulations.

Advice to stand out and make a successful application

Use the CV to show specific Python and analytics work, including the data problem, modelling choices, validation approach and result. Examples involving missing data, simulation or production-ready analytical tools would connect closely to the role. In interviews, explain how you would assess sector alignment while documenting assumptions and communicating uncertainty to non-data specialists. If you have climate experience, make the link to portfolio analysis or sector pathways explicit; otherwise, demonstrate a clear understanding of why bank lending data can inform transition assessments.

What aspects of the company's sustainability is this role likely to focus on?

The sustainability focus is climate alignment of the bank’s lending portfolio, with analysis covering emissions-intensive sectors and the stated goal of financing pathways consistent with net zero by 2050. The work supports measurement of portfolio exposure against climate objectives and informs sector-level strategy. The posting does not describe direct emissions-reduction projects at client sites. Its contribution is analytical: improving methods, indicators and tools that could help banking teams assess transition progress and portfolio impacts.

What are the main challenges someone in this role might face?

The role must address uneven data coverage and sector-specific methodology while producing credible, repeatable portfolio assessments. Choices about assumptions and missing values could materially affect reported alignment, so transparency and careful validation are likely to matter. It may also be challenging to convert technical results into clear guidance for banking teams and to scale analytical processes without losing methodological consistency.

How could a typical day look like for someone in this position?

A day might begin with checking datasets and running Python analyses for one or more sector alignment assessments. The data scientist could then review simulation outputs, test a methodology update or document how a missing-data approach affects portfolio indicators. Time may also go to discussions with sector experts and banking colleagues, dashboard improvements and coordination on GoNetZero industrialisation. The balance is likely to shift between technical work and cross-team interpretation.

What are the opportunities for professional growth and development in this role?

The position could build a focused profile in climate analytics and sustainable finance, with experience spanning portfolio data, sector pathways and internal analytical products. Collaboration with banking and sector teams may also strengthen the ability to explain technical findings in a strategic context. Potential next steps could include leading larger analytics projects, specialising in a high-emitting sector or moving into broader climate-finance strategy. The source describes development and network exposure but does not specify a promotion path or formal training scheme.

The main stakeholders you might be interacting with

The main stakeholders are C2A Data Analytics colleagues, sector experts, the Global Banking front office and the Low Carbon Transition Group. The role also supports shared work across Group and Corporate and Institutional Banking. Their interactions could centre on data and methodology choices, interpreting portfolio simulations, refining climate indicators and developing the internal dashboard. Banking teams may use the resulting analysis to inform client transition discussions and sector strategy.

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