Data Scientist en Compasslexecon

About Compass Lexecon Compass Lexecon is a world-leading economic consultancy. We advise on economic issues related to competition policy, economic and financial regulation, public policy, intellectual property and the assessment of damages, across all industries. With more than 700 professionals, including 170+ Ph.D. economists, based in 25 offices around the world, Compass Lexecon offers a global perspective on economic matters. Our economists produce creative, compelling solutions, underpinned by rigorous economic thinking and cutting-edge analysis. We have advised clients in matters before regulatory agencies and courts in over 120 jurisdictions. The Compass Lexecon International team in EMEA, Asia Pacific and Latin America comprises over 350 economists and academic affiliates based across 17 offices. Our diverse group of experts is known for its integrity, creative thinking, and exceptional quality work. They bring a diverse set of skills and experience in empirical analysis, combined with deep sector expertise and supported by cutting-edge data science tools and techniques. We are committed to being an equal opportunities employer and welcome applications from all suitably qualified persons regardless protected characteristics. We believe that working in diverse teams, where everybody’s views are considered and respected, helps us to deliver work of the highest standards of quality and integrity.  Overview/About the Role Compass Lexecon is recruiting Data Scientists with hands on experience in data engineering workflows to join the Data team part of the broader Research Team. Data is a core part of every project at Compass Lexecon and turning that data into compelling empirical analysis is fundamental to what we do. With increasing amounts of data being generated, there are exciting opportunities to apply tools from data science, machine learning, and data engineering to the interesting policy and competition questions that arise in our work.  The team aims to (a) advance our thought leadership in the industry by introducing new tools and techniques to address challenges encountered in economic consulting, bringing Compass Lexecon to the forefront of data analytics, and (b) broaden and deepen all Compass Lexecon economists’ specialist skillsets to offer our clients the most effective, creative and cutting-edge analysis and advice. In doing so, we aim to push the frontier of how data is used to shape markets in some of the world’s most important industries.

Key Responsibilities:

Work on client-facing projects, designing and implementing complex data science solutions, from concept to productions to solve real-world competition and regulatory challenges faced by businesses. Each project is different - one week, you might solve a data engineering challenge, which could involve mining large datasets. The next week, you may find yourself working on natural language processing using large language models, developing innovative AI applications.

Contribute to cutting-edge research projects, advancing Compass Lexecon’s thought leadership in the application of advanced analytics to competition and finance cases.

Conduct advanced training sessions and develop sophisticated tools to enhance how economists work with data.

Qualifications and Experience Required:

Master’s degree in data science, computer science, applied mathematics, statistics, machine learning, economics, or operations research.

At least 2 years of professional data science experience, with a proven track record of translating business problems into data science solutions.

Proficiency in Python, R, and SQL, with experience developing production-level code and working effectively with relevant libraries and frameworks, as well as hands-on proficiency with NoSQL databases such as MongoDB.

Possess practical experience with a range of data science methods and concepts, such as data engineering workflows, machine learning, natural language processing, with the ability to quickly learn new tools as needed.

Hands-on experience with cloud computing platforms (Azure, AWS, or GCP) and container technologies (such as Docker) in collaborative project environments.

Solid understanding of data engineering principles including data modelling, ETL processes, and building data pipelines.

Strong organizational skills, able to independently manage multiple projects and deliverables on time.

Excellent teamwork and communication skills, with demonstrated ability to share knowledge and present findings clearly to both technical and non-technical colleagues.

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