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About the Role

As a Quantitative Analyst at ICIS, you will drive data-based innovation and complement our technical capability to operationally deploy and maintain Data Science models and model interfaces in the energy and chemicals industries. You will join an experienced team of Data Scientists and work closely with market experts globally. Your primary focus will be to design, improve, and maintain models and Python (Dash) applications for augmented energy pricing processes.

Responsibilities

Maintain and enhance applications in Python (Dash) to integrate Data Science models.
Drive and support R&D and operation of data-driven analytical market models.
Co-develop quantitative market models to predict key market variables.
Guide and support others in model development and implementation.
Implement new models and model enhancements, including cloud-based model and process automation.
Engage with internal market experts to explain models and insights.
Translate domain knowledge back into models and build a deep understanding of operations.
Drive maintenance and improvements of the code base and code structure for operational models and backend data architectures.
Develop, test, and roll out new application functionality and change requests.
Manage operational models & applications, including monitoring, refactoring, and updating live services.
Review and debug code and ensure good code documentation.
Enable efficient communication across teams through fast prototyping and demos.
Expand knowledge by learning new techniques and applying them to analytical problems.
Actively share knowledge and innovation areas with peers.

Requirements

Minimum of 3 to 5 years of practical experience as a software engineer, preferably in markets and market prices.
Excellent Python skills and experience with Python packages for applications (such as Dash).
Professional use of version control tools in projects involving several developers.
Experience with designing and managing containerized applications.
Familiarity with cloud platforms (e.g. AWS).
Data handling and data modeling knowledge and experience using relational databases (e.g. PostgreSQL).
Holistic perspective on business value from analytics.
Strong ability to explain complex topics to diverse stakeholders.
Preferably previous exposure to Data Analytics or Data Science.
Interest in working on analytics and forecasting projects heavily reliant on human / machine collaboration.

Skills

Python
Dash
Version control tools
Containerized applications
Cloud platforms (AWS)
Relational databases (PostgreSQL)
Data handling
Data modeling
Analytics
Forecasting

Location

Germany - Karlsruhe

Work Type

Full-time
Hybrid

Experience Level

3-5 years

Salary/Compensations

€59,300 - €98,600

Benefits

Fitness studio
20 days work from anywhere
2 days additional leave for social engagement
Country specific benefits

About the Company

ICIS is part of Lexis Nexis Risk, a division of RELX Group, a FTSE 20 company with revenues of $12.9 billion in 2025 and an employee base of over 30,000 people across 40 countries.
ICIS provides data services, thought leadership, and decision tools to make energy, petrochemical, and fertilizer industries' markets more trusted and predictable.
Our intelligence supports thousands of daily decisions across supply chains.
We have a global presence with over 700 employees based in multiple international locations.
LexisNexis Risk Solutions provides innovative technologies, information-based analytics, decisioning tools, and data management services.
LexisNexis Risk Solutions is part of RELX, a global provider of information and analytics.

Equal Opportunity

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.
We are committed to Diversity and Inclusion.
Qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.