Energy & Climate Analytics Modeler, Associate - Aladdin Financial Engineering

Business Unit Overview: 

Our Energy and Climate Analytics (ECA) team is responsible for building analytics and capabilities that are needed to quantify the impacts of energy policy, natural hazards, natural capital, and other geospatial factors on financial assets. We also develop the architecture and software used for production and delivery of analytics to portfolio and risk management professionals both within and outside BlackRock via the Aladdin® software platform. 

Given the diversity of skills required to develop these products, ECA brings together professionals from a wide range of domains spanning meteorology, hydrology, energy systems modeling, economics, financial engineering, and computer science; and spanning functions including modeling, analytics, and data engineering. As part of ECA, you will be working with clients and partners to develop quantitative models to assess the financial impacts of shocks from weather and climate, energy policy, and other geospatial risk factors on a wide range of asset classes including corporate equity and fixed income, mortgage-backed securities, municipal bonds, sovereign bonds, as well as on investments in private markets such as infrastructure and real estate. As energy, weather and climate, and other geospatial sources of investment risk become an ever-increasing focus for investors, you will be developing models and analytics to help drive a deeper understanding of risks and opportunities in this space. We partner with stakeholders from a range of teams within BlackRock and from external Aladdin® clients to support multiple use cases including regulatory reporting, risk management, and portfolio construction. 

Job Purpose/Background: 

We are seeking a highly skilled, motivated, and curious individual to join our team as Quantitative Researcher with a focus on Geospatial Data Science. In this role, you will be responsible for leveraging a range of geospatial datasets, including related to weather and climate risks, to provide insights and support financial decision-making processes. You will work closely with cross-functional teams to analyze data, develop models, create visualizations, and deliver analytics that drive strategic initiatives and business growth. 

Key Responsibilities: 

• Analyze geospatial data including related to weather and climate risks; identify trends, patterns, and anomalies; and develop models to quantify how they have impacted financial performance for a range of public asset classes. 

• Develop, implement, and maintain models and workflows to forecast financial outcomes due to weather and climate risks, and from other geospatial risk sources. 

• Carry out necessary quality control, model governance, software development standards, and support production implementation for successful models. 

• Collaborate with cross-functional teams to integrate geospatial analytics into financial modeling, software tools, and decision-making processes. 

• Create visualizations, do presentations, and write reports to communicate findings to stakeholders. 

• Stay updated with the latest advancements in climate risks, geospatial data and modeling, and related financial modeling methodologies. 

Skills & Qualifications: 

• Bachelor's degree (+4 years of professional experience), Master's degree (+2 years of professional experience), or PhD in Environmental Engineering, Environmental Science, Applied Mathematics, Geospatial Data Science, Financial Engineering, Operations Research, Computer Science, Physics, or a related engineering or quantitative field. 

• Proven experience analyzing and building models using geospatial data including working with vector and raster formats. 

• Strong knowledge of probability and statistical modeling, including econometric methods. 

• Proficiency working with Python including common data science libraries (e.g., pandas, numpy, scipy, statsmodels), as well as geospatial data science libraries (e.g., geopandas, xarray). 

• Strong analytical and problem-solving skills, with the ability to interpret complex datasets and provide actionable insights. 

• Ability to work independently and collaboratively in a fast-paced, dynamic environment. 

• Excellent communication and presentation skills, with the ability to convey technical information to non-technical stakeholders. 

• Curiosity to continue learning about different domain and technical subjects relevant to the position. 

Nice if you have: 

• Experience working with gridded weather and climate datasets (e.g., reanalyses, weather forecasts, seasonal forecasts, climate model projections) and modeling natural hazards (e.g., flooding, wildfires, tropical cyclones). 

• Knowledge of financial markets and experience in financial modeling (e.g., factor risk modeling, asset valuation, credit risk). 

• Experience working with cloud computing platforms and implementing parallelization workflows (e.g., using zarr and dask on a cloud cluster). 

• Experience with AI and machine learning modeling methodologies, including leveraging LLMs for analyzing text files.  

• Experience with geospatial analysis software such as ArcGIS or QGIS, and tools like GDAL. 

• Proficiency in data analysis tools and other programming languages in addition to Python such as R or SQL.