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Data Scientist F/H - CDI - Montpellier

Qui sommes-nous ?

Q ENERGY France est un acteur majeur du marché des énergies renouvelables en France avec plus de 25 ans d'expérience dans le développement, la construction et l'exploitation de projets éoliens et photovoltaïques. Nous comptons plus de 200 employés et 7 agences régionales ainsi qu'un siège social basé à Avignon. Rejoignez-nous dans cette aventure passionnante et contribuez à faire une différence durable pour notre planète.

Q ENERGY est la société européenne d'énergie verte à 360°. Avec plus de 500 employé.e.s, nous développons, construisons et gérons des actifs d'énergie renouvelable sur l'ensemble de la chaîne de valeur des projets à grande échelle - du solaire à l'éolien terrestre et offshore, en passant par le stockage d'énergie et les centrales hybrides. Avec un pipeline de plus de 16 GW, nous comptons parmi les leaders des énergies renouvelables en Europe. Nous sommes toujours à la recherche de talents souhaitant nous rejoindre pour contribuer à un monde durable alimenté par l'énergie verte.

Rattachement

Hiérarchie : Le poste reporte à l'Expert en Ingénierie et Analyse Business.

Transversal : Relation étroite avec la Division de Transformation Digitale, en particulier avec l'équipe Application & Data pour l’ingénierie des données, ainsi qu’avec les départements métiers pour comprendre les enjeux business.

Missions

  • Comprendre les problématiques métiers et savoir les traduire en analyses, réaliser des études, interpréter, modéliser et présenter les résultats via des outils de data visualisation.
  • Extraire et structurer les données pour les analyses.
  • Analyser les données, produire des tableaux de bord et aider les interlocuteurs métiers à poser les bonnes questions pour favoriser la prise de décision grâce à un bon storytelling.
  • Créer des outils de modélisation pour l’optimisation multiparamétrique, la physique (propagation acoustique…), l’analyse technique et/ou économique…

Exemples de projets liés au poste

  • Prévision des prix des offres concurrentes dans les appels d’offres.
  • Prévision du prix de capture pour les énergies renouvelables.
  • Modélisation et optimisation de projets hybrides comme l’association Hydrogène + centrale solaire ou parc éolien.
  • Optimisation de projets en prenant en compte plusieurs contraintes (rendement + réglementation acoustique, taille du stockage + production & prix de l’électricité…).
  • Fourniture d’analyses techno-économiques pour aider le management dans l’analyse du portefeuille de projets et l’évaluation des risques.

HSE 

  • Contribuer à la culture Santé, Sécurité et Environnement de l’entreprise en :
    • Réalisant son travail dans le respect des mesures préventives mises en place par l’entreprise et définies dans l’évaluation des risques globaux, les politiques HSE, les procédures, modes opératoires et guides.
    • Déclarant tout événement ou situation pouvant représenter un danger pour les personnes (collègues et prestataires) et/ou l’environnement.
    • Participant aux formations et actions de sensibilisation sur ces thématiques.

QUALITÉ 

  • Respecter et appliquer la politique et les procédures qualité de l’entreprise.
  • Participer à la mise à jour des documents du système de management de la qualité.
  • Déclarer les non-conformités et contribuer à la mise en œuvre des actions correctives.
  • Participer aux actions et projets d’amélioration continue et de partage des connaissances.

Profil

  • Trois ans ou plus d’expérience en extraction et analyse de données en tant que Data Analyst.
  • Compétences avérées en analyse, incluant l’exploration, l’évaluation et la visualisation des données à l’aide de statistiques et de machine learning.
  • Excellentes compétences en communication et collaboration, en anglais et en français.

Compétences Techniques

  • Maîtrise des langages d’analyse et de manipulation de données (SQL, Azure SQL, MongoDB, …).
  • Langages de programmation (R ou Python).
  • Outils de data visualisation (Power BI, Tableau, …).
  • Expérience avec les outils et frameworks ETL (Airflow ou Data Fabrics).
  • Expérience avec les plateformes cloud telles qu’Azure, AWS ou Google Cloud.
  • Modélisation et analyse des données à l’aide de statistiques ou d’algorithmes de machine learning.

Compétences comportementales

  • Pédagogie, capacité de persuasion et excellentes compétences en communication orale et écrite.

Comment faisons-nous la différence ?

 

·         Des valeurs fortes et incarnées

·         Un management de proximité

·         Une dynamique d’organisation apprenante

·         Une entreprise en constant développement

·         Valorisation et développement des compétences

 

Nos avantages sociaux :

 

·         Flexibilité et bien-être : jusqu'à 2 jours de télétravail et flexibilité des horaires

·         4 Jours de congés par an offerts pour des actions de bénévolat

·         L’abondement de vos dons aux associations à hauteur de 500€ par an

·         Forfait mobilité durable pour les déplacements en mobilité douce (vélo...) ou en covoiturage et aides à l’écomobilité

·         Titres restaurants (9€ pris en charge à 50% par la société)

·         Activités “bien-être” et évènements régulièrement proposés par le CSE

 

Nous concourrons à créer un environnement professionnel fondé sur le respect et la bienveillance, en réunissant des personnes d'horizons différents pour qu'elles nous apportent des idées novatrices et de nouvelles perspectives. Nous œuvrons à la réalisation de notre stratégie en matière de diversité et d'inclusion afin de garantir l'égalité des chances et nous accompagnons les parcours professionnels de toutes et tous.

 

Q ENERGY France s'engage à examiner toutes candidatures à compétences égales.  Nous sommes soucieux d'adapter notre processus de recrutement et d'intégration aux personnes en situation de handicap.

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What You Should Know About Data Scientist F/H - CDI - Montpellier, Q-Energy

At Q ENERGY France, we're on a mission to make a substantial impact in the renewable energy sector, and we're thrilled to invite applications for the Data Scientist F/H position in Montpellier! With over 25 years of expertise in developing, constructing, and managing wind and solar projects, our 200+ strong team plays a pivotal role in a sustainable future. As a Data Scientist, you'll be at the heart of our Digital Transformation Division, working closely with the Application & Data team to analyze and model business challenges into actionable insights. Your role will involve extracting, structuring, and interpreting data, creating insightful visualizations to empower our collaborators in making informed business decisions. The variety of projects you'll tackle is exciting—from forecasting competitive bid prices to optimizing hybrid projects involving hydrogen and solar solutions. With an impressive pipeline exceeding 16 GW, our innovative approach keeps us at the forefront of the renewable sector in Europe. We're keen on finding a team player with at least three years of experience in data analysis, proficiency in SQL and Python, and excellent communication skills in both English and French. Join us, and let’s shape a sustainable future together at Q ENERGY!

Frequently Asked Questions (FAQs) for Data Scientist F/H - CDI - Montpellier Role at Q-Energy
What are the key responsibilities of a Data Scientist at Q ENERGY France?

As a Data Scientist at Q ENERGY France, your core responsibilities will involve translating business challenges into data analyses, structuring and extracting data for in-depth analysis, and creating compelling visualizations to facilitate effective decision-making. You'll collaborate closely with multiple departments, ensuring that our insights are data-driven and support our renewable energy projects.

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What qualifications do I need to apply for the Data Scientist position at Q ENERGY France?

To qualify for the Data Scientist position at Q ENERGY France, candidates should possess a minimum of three years of experience in data extraction and analysis. Proficiency in SQL and Python, along with experience in data visualization tools such as Power BI or Tableau, is also essential. Strong communication skills in both French and English are necessary to collaborate effectively within our multicultural team.

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How does the Data Scientist role contribute to Q ENERGY's projects?

The Data Scientist role at Q ENERGY is crucial for the success of our renewable energy projects. You'll analyze data to forecast energy prices, optimize hybrid solutions, and conduct techno-economic analyses that aid management decisions regarding project portfolios. Your insights will support the strategic planning necessary for our growth and sustainability.

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What technical skills are essential for a Data Scientist at Q ENERGY France?

Candidates must display strong technical skills including data manipulation linguistics like SQL, experience with programming languages such as Python or R, and familiarity with cloud platforms like Azure or AWS. Knowledge of ETL tools and data visualization techniques are also crucial to effectively deliver insights that support our renewable initiatives.

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What are the professional development opportunities for a Data Scientist at Q ENERGY?

At Q ENERGY France, we value continuous learning and development. As a Data Scientist, you will have opportunities to participate in various training sessions, engagement in learnings related to industry trends, and projects that foster knowledge-sharing. We strive to create an environment where you can grow your skills while contributing to meaningful work in the renewable energy sector.

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Common Interview Questions for Data Scientist F/H - CDI - Montpellier
How have you used data visualization in past projects?

When answering this question, highlight specific tools you've used, describe how you approached the visualization process, and illustrate the impact your visualization had on decision-making. It's vital to convey how you translate complex data into easily digestible visuals that drive business outcomes.

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Can you explain a time when your data analysis directly influenced a business decision?

Prepare to share a compelling and specific example, detailing the context, what data you analyzed, your methodology and the stakeholders involved. Emphasize the outcome and how it benefited the organization, showcasing your analytical and problem-solving capabilities.

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What programming languages are you most comfortable with?

Discuss your experience with programming languages relevant to the Data Scientist role, such as Python or R. Provide examples of projects or tasks where you utilized these languages effectively, focusing on data manipulation, analysis, and visualization.

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How do you approach a new data science project?

Explain your structured approach, such as understanding the business question, conducting exploratory data analysis, selecting the right methodologies, and delivering actionable insights. Highlight your emphasis on collaboration with stakeholders to ensure alignment with business objectives.

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Describe how you keep up with the latest developments in data science.

Talk about your commitment to continuous learning through online courses, workshops, reading industry publications, or participating in relevant conferences. Illustrate how this knowledge has positively impacted your previous work.

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What experience do you have with statistical modeling?

Discuss specific statistical methods or models you've used and the context in which you applied them. This might include regression analysis, clustering, or time-series forecasting. Be ready to explain your results and how they influenced your work.

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How would you handle a situation where the data doesn't support the expected outcome?

Focus on your analytical mindset, discussing your methods for investigating data discrepancies and how you've communicated findings to stakeholders. Stress the importance of transparency and using such experiences as learning opportunities.

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Can you give an example of a multi-parameter optimization you've worked on?

Provide a detailed scenario where you applied optimization techniques, explaining the parameters considered and how you approached the optimization process. Highlight the tools and methodologies you employed to achieve the desired results.

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What are your experiences with machine learning?

Highlight your experience with machine learning algorithms, discussing specific projects where you've implemented them. It's useful to explain your approach to selecting algorithms based on business needs and data types, along with the results achieved.

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How do you prioritize competing projects with tight deadlines?

Discuss your organizational skills and time management strategies. It's important to illustrate how you assess project scope and urgency, communicate transparently with stakeholders, and ensure that you deliver high-quality work consistently.

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SENIORITY LEVEL REQUIREMENT
TEAM SIZE
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EMPLOYMENT TYPE
Full-time, remote
DATE POSTED
April 10, 2025

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