Senior Data Scientist Freelance

Résumé du poste
Freelance
Paris
Salaire : Non spécifié
Télétravail occasionnel
Compétences & expertises
Contenu généré
Sens des affaires
Empathie
Snowflake
Sql
Tick
+5
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Swan
Swan

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Le poste

Descriptif du poste

Swan has reached a level of maturity where Artificial Intelligence can significantly enhance our product, operations, and risk management.

We are currently seeking a detail-oriented and adaptable Data Scientist to join our dynamic team for a specific project over a few months. In this role, you will play a pivotal part in interpreting and analyzing complex data to drive strategic decision-making and advance our innovative projects.

As part of our team, you will work on impactful projects such as developing in-house ML models and utilizing these technologies to gain deeper insights into market dynamics, optimize operations, and enhance customer experiences.

The ideal candidate will possess expertise in data manipulation, machine learning, and statistical analysis.

Key responsabilities:

  • Deliver impactful projects leveraging ML to optimize the business - such as Operation automation, Fraud detection and Compliance control optimization

  • Develop comprehensive data models and algorithms to predict, optimize, and solve various business problems.

  • Manipulate and analyze complex, high-volume data from varying sources using a range of tools and data analysis techniques.

  • Design and implement robust analytical models aimed at improving business outcomes.

  • Collaborate with cross-functional teams to build scalable and repeatable data-driven solutions that enhance product development, marketing strategies, and customer experiences.

  • Maintain an understanding of industry trends and use this knowledge to suggest, innovate, and implement new technologies.

  • Handle the processing and analysis of new data sources and experimental data, ensuring data quality and accuracy.

Our stack: SQL, Python, Snowflake, AWS, DBT

Your team:

Reporting to Romain, our VP of Data, you will join our new Data team, which includes a Data Engineer, a Data Analyst, a Data Analytics Engineer and a Product Data Analyst.

This is an exciting opportunity to become part of a dynamic and growing team, making a significant impact on the future success of Swan.


Profil recherché

You’re a great match if:

  • 5/10+ years of experience in Data Scientist, with a preference for prior involvement in the fintech industry and/or B2B SaaS environments.

  • Ideally PHD in Applied Mathematics, Statistics, Computer science Machine learning. At least master degree in those fields.

  • Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch)

  • Expertise in data mining techniques and statistical analysis tools like Python, SQL.

  • Demonstrated ability to effectively manage projects and engage with stakeholders.

  • A commitment to team spirit, transparency, and trustworthiness is important, as we value a collaborative and supportive company culture.

  • Autonomy, a “Can-do” spirit, and the ability to take initiative and ownership of your work are required.

  • Passion, curiosity, and the capacity to learn quickly are important, as we are constantly exploring new technologies and approaches to improve our work.

  • Strong problem-solving skills and business acumen

  • Our ideal teammate: Empathetic. Skilled. Frank. We love to challenge each other, and we leave our egos at the door.

It’s okay if you don’t tick all the boxes — don’t let imposter syndrome prevent you from applying! 🙌

Swan is committed to providing a caring work environment for all employees, regardless of age, sex, disability, sexual orientation, race, religion, or belief.

When it comes to recruitment, we’re interested in your work experience, skills, and overall personality. Because diversity makes the workplace stronger and is necessary for Swan’s success, we are intensifying efforts to incorporate concrete actions to help us improve in this area.


Déroulement des entretiens

  • A 30-min video call with our Talent Acquisition Manager, to get to know you, understand your career expectations and answer your questions

  • An interview with your future manager

  • Case study

  • An interview with the team

  • Last interview with our Chief Product officer

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