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Data scientist France Jobs (Hybrid work)

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Senior Blockchain Data Scientist
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Join Ledger in Paris as a Senior Blockchain Data Scientist. Leverage your expertise in SQL, Python, and data pipelines (dbt, Airflow) to analyze complex on-chain data and drive strategic decisions. Enjoy flexible remote work, health insurance, and equity in a leading Web3 company.
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France , Paris
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Not provided
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Ledger
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Until further notice
Senior Data Scientist
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Join a dynamic R&D team in Paris as a Senior Data Scientist. Apply your 3+ years of AI/ML experience in Python/R to design and industrialize advanced models. Work on impactful projects in sectors like Energy or Health, with flexible hours and a central office location.
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France , Paris
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Artelys
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Until further notice
Underwriter Data Scientist - Industrial risks
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Join our growing team in Paris as an Underwriter Data Scientist for Industrial Risks. You will develop innovative risk models using Python and data science to structure and price insurance products. This role requires fluency in French and English, with 2-5 years of underwriting or related experi...
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France , Paris
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Descartes Underwriting
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Data Scientist
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Join our Data Science team in Paris to model climate risks and develop innovative parametric insurance products. Utilize Python and machine learning to analyze natural perils like wildfires and earthquakes for global clients. This role offers professional growth in a collaborative, international ...
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France , Paris
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Not provided
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Descartes Underwriting
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Until further notice
Explore the dynamic and in-demand field of data science and discover the vast array of data scientist jobs available. A Data Scientist is a professional who uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from both structured and unstructured data. They are the detectives of the digital age, solving complex business problems by turning raw data into actionable intelligence. The core objective of the role is to empower organizations to make data-driven decisions, optimize operations, and innovate products and services. Typically, the responsibilities of a Data Scientist encompass the entire data lifecycle. This begins with data acquisition and cleaning, where they gather data from various sources and prepare it for analysis, a critical step often involving building and maintaining robust data pipelines. Following this, they perform exploratory data analysis to identify patterns, trends, and anomalies. A significant part of their work involves developing and implementing machine learning models and statistical models for purposes such as prediction, classification, clustering, and recommendation. They are also responsible for communicating their findings effectively through data visualizations, dashboards, and reports, translating complex technical results into clear, actionable recommendations for stakeholders across the business, including product, engineering, and finance teams. To succeed in data scientist jobs, a specific skill set is required. Proficiency in programming languages, particularly Python and/or R, is fundamental, along with expert-level skills in SQL for data manipulation and extraction. A strong foundation in statistics and mathematics is crucial for understanding and building models. Practical experience with machine learning libraries (like scikit-learn, TensorFlow, or PyTorch) and data visualization tools (such as Tableau, Power BI, or matplotlib) is highly valued. Beyond technical prowess, soft skills are equally important. Data scientists must possess critical thinking and problem-solving abilities to frame business challenges as analytical problems. Excellent communication and storytelling skills are essential for conveying insights to both technical and non-technical audiences, ensuring that data-driven strategies are understood and implemented. Common requirements for these positions often include a degree in a quantitative field such as Computer Science, Statistics, Mathematics, or Engineering. While entry-level roles exist, many data scientist jobs seek candidates with proven experience in handling data, building models, and delivering measurable impact. The field is constantly evolving, so a passion for continuous learning about new algorithms, tools, and domains is a key trait of successful professionals. If you are analytical, curious, and driven to find answers hidden within data, exploring data scientist jobs could be your ideal career path.

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