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Tech Lead – Advanced Analytics

TotalEnergies -
Genève, GE

Soumettre votre candidature

Détails de l'emploi

CDI
Il y a 12 heures

Qualifications

CI/CD
Gestion du personnel
Niveau Doctorat
Relational databases
Niveau Master
Bases de données
SQL
AWS
Esprit d'analyse
Docker
Mentorat
Développement logiciel
GitHub
Leadership
Compétences en communication
Python

Description complète du poste

Contexte et environnement

The Advanced Analytics team is part of the Power & Gas Trading IT department and develops software products that enable advanced quantitative analytics across European and Worldwide energy markets.

Our mission is to build scalable, production-grade applications supporting Traders, Quantitative Analysts and Market Analysts in forecasting, optimization, simulation and data analysis. Working closely with quantitative teams, we transform analytical and machine learning models into robust software products capable of operating reliably in production while remaining flexible for future evolution.

As a Tech Lead, you will provide technical leadership across the Advanced Analytics product landscape. You will combine hands-on software engineering with architectural thinking, guiding technical decisions, promoting engineering excellence, and partnering with quantitative stakeholders to deliver high-quality analytics platforms.

This is not a people management role. Success in this position comes from technical expertise, influence, mentoring and the ability to drive engineering best practices across multiple initiatives.

Activités

As a Tech Lead, your main responsibilities will be to:

Lead the technical design and implementation of software products supporting forecasting, optimization, simulation and advanced analytics use cases.
Drive software architecture and technical decisions in collaboration with Solution Architects, ensuring consistency, scalability, security and maintainability across the Advanced Analytics landscape.
Partner closely with Quantitative Analysts, Traders and business stakeholders to understand, challenge and refine functional and technical requirements.
Translate quantitative research into reliable, production-ready software solutions while ensuring long-term maintainability and extensibility.
Design cloud-native applications following modern engineering principles and best practices for reliability, observability, security and cost optimization.
Lead the industrialization of analytical and machine learning models, ensuring reproducibility, scalability, monitoring and operational excellence.
Contribute to software development, code reviews, technical investigations and complex implementations.
Promote engineering excellence through coding standards, automated testing, CI/CD, documentation and continuous improvement.
Mentor and support engineers through technical coaching, architectural guidance and knowledge sharing, without direct line management responsibilities.
Support production systems, troubleshoot complex technical issues and drive continuous improvement of existing applications.

In addition, the Tech Lead will be expected to:

Own technical decisions from solution design through production delivery.
Establish and promote engineering standards across the Advanced Analytics team.
Balance short-term delivery objectives with long-term architectural sustainability.
Make sound technical decisions in environments with evolving requirements and incomplete information.
Identify technical risks early and propose pragmatic, scalable solutions.
Drive adoption of modern software engineering practices and emerging technologies where they provide tangible business value.
Build credibility with both software engineers and quantitative experts by combining strong engineering capabilities with an understanding of analytical modelling challenges.
Influence technical direction through collaboration, expertise and leadership rather than formal authority.

Profil du candidat

Education

Master's degree in Computer Science, Software Engineering, Mathematics, Physics, Engineering or related technical discipline.

Experience

Minimum 6 years of professional experience in software development, data science or related fields, including experience acting as a technical lead or senior technical contributor on complex software products.
Experience deploying, operating and maintaining analytical or machine learning solutions in production environments.
Experience working in Agile product teams within complex enterprise environments.
Experience working in the energy trading industry, particularly in power markets, would be considered an advantage.

Technical Skills

Expert-level proficiency in Python and experience building production-grade backend applications.
Strong experience designing cloud-native applications and distributed systems on AWS.
Strong understanding of software architecture, design patterns, API design and system integration.
Experience designing RESTful APIs and event-driven architectures.
Experience with containerization technologies such as Docker and orchestration platforms including Kubernetes and ECS.
Experience implementing CI/CD pipelines and Infrastructure as Code.
Solid understanding of relational databases, SQL, data modelling and modern data platform architectures.
Hands-on experience with Databricks, MLflow or comparable modern data and MLOps platforms.
Strong knowledge of software engineering best practices, including automated testing, code reviews, observability and production support.
Familiarity with Lakehouse architectures and modern Data Engineering practices would be an asset.
Experience developing modern frontend applications and data visualization tools using React, or similar frameworks, would be considered a plus.

Skills

Excellent communication and stakeholder management skills, with the ability to interact effectively with both technical and quantitative audiences.
Strong analytical and problem-solving capabilities.
Demonstrated ability to mentor engineers and provide technical leadership through influence.
Ability to work effectively in a fast-paced, collaborative and international environment.
Strong commitment to engineering excellence and continuous improvement.

Additional Information

Preferred qualifications include:

PhD in Computer Science, Mathematics, Physics, Operations Research, Machine Learning, Artificial Intelligence or another quantitative discipline.
Understanding of European energy systems, electricity markets and quantitative trading workflows.
Experience with forecasting, optimization, time-series analysis or other quantitative modelling techniques, together with an understanding of the challenges involved in bringing analytical models into production.
Experience building data-intensive or AI-enabled platforms supporting quantitative research.
Knowledge of MLOps best practices, including model lifecycle management, model versioning, reproducibility, monitoring and governance.
Experience leveraging AI-assisted software development tools (e.g. GitHub Copilot, Claude Code, Codex or equivalent) to improve engineering productivity while maintaining high standards of software quality.

Informations supplémentaires

TotalEnergies valorise la diversité, promeut le développement individuel et offre des opportunités d'emploi égales à tous les candidats.

Become one of the drivers of energy transition with TotalEnergies Trading & Shipping.

TotalEnergies is a broad energy company that produces and markets energies on a global scale: oil and biofuels, natural gas and green gases, renewables and electricity. Our 105,000 employees are committed to energy that is ever more affordable, clean, reliable and accessible to as many people as possible. Active in more than 130 countries, TotalEnergies puts sustainable development in all its dimensions at the heart of its projects and operations to contribute to the well-being of people

Trading Shipping :
Give your best to better energy and make the commitment with TotalEnergies. We are one of the most active players in the international oil markets, trading with a vast network of customers and suppliers worldwide: national oil companies, producers, other oil majors, refiners, traders, distributors and end-users.
We have developed a set of trading strategies and expertise, which allows us to respond permanently to market changes and opportunities, on all physical and paper oil markets.
Satisfying the energy needs of a growing world population, curbing global warming, and adapting to changing customer behaviors and expectations are the three challenges that TotalEnergies must meet over the next 20 years. With its biomass blending and trading activity, TotalEnergies Trading & Shipping is an active participant in the development of sustainable biofuels. Our maritime transport expertise also helps to reduce the carbon footprint of sea transportation and we recently announced the time chartering of new vessels equipped with LNG propulsion.

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