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Senior Data Scientist

About Satispay
At Satispay, we're not just reimagining payments; we're pioneering a movement toward simplicity and accessibility. Picture yourself at the forefront of innovation, leading the way in revolutionizing payments - and beyond! - across Europe, alongside a vibrant community of like-minded individuals driven by a shared vision: simplifying payments to improve everyone’s life.

Are you ready to be part of something bigger? Satispay is the place for you! Come be part of our dynamic team and help us shape the future of payments in Europe.

🚀 Join us as a  Staff Engineer and let's make magic happen together.

Role Overview
As a Senior Data Scientist, you will drive fintech innovation by developing predictive models and data-driven solutions to optimize products and enhance business outcomes. You’ll work closely with teams to integrate machine learning models into production and help shape the future of the Satispay ecosystem.

Your mission:

  • Deliver impact in fintech innovation. Develop and implement data-driven solutions to shape and optimize product lines, directly contributing to customer and business success.

  • Analyze and drive insights. Explore and interpret datasets to uncover actionable insights, influencing product design and financial decision-making processes.

  • Design predictive systems. Create and optimize predictive models for fraud and credit risk to enhance the reliability and accessibility of current and prospect offerings.

  • Deliver and maintain production-ready systems. Ensure seamless integration of analytic pipelines and machine learning models into production, focusing on system reliability, ongoing maintenance, and continuous training to adapt to changing data and business requirements.

  • Collaborate and integrate. Work closely with product managers, engineers, and other teams to incorporate data science solutions into Satispay ecosystem.

  • Stay ahead of trends. Continuously research and adopt cutting-edge techniques and tools to ensure a competitive edge in the fintech landscape.

  • Enhance a data-driven culture. Support decision-making and foster a data-first mindset by delivering clear, actionable insights across the organization.

Your ideal profile:

  • Proven experience in data science and fintech. You hold a Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field, paired with 3+ years of experience in data science, analytics, or a similar discipline. Ideally, your background includes work in financial services, payments and credit risk modeling.

  • Technical excellence. You bring extensive experience with Python or R and are well-versed in machine learning libraries such as Scikit-learn, TensorFlow, or PyTorch. Strong skills in SQL and query optimization are considered as a plus.

  • Modeling and problem-solving expertise. You have a proven track record in predictive modeling, statistical analysis, and machine learning techniques, including supervised and unsupervised learning.

  • Experience in fintech: Familiarity with financial services, credit risk modelling and payments is a strong plus.

  • Cloud platform proficiency. You have experience deploying machine learning models on cloud platforms such as AWS, Google Cloud Platform, or Azure.

  • Detail-oriented and communicative. You have a sharp eye for detail and the ability to execute complex projects. You communicate effectively, building trust and understanding across technical and non-technical stakeholders.

  • Passion for fintech and innovation. You are enthusiastic about working in dynamic, innovative environments where your work directly shapes financial products.

  • Adaptability and continuous learning. You thrive in a fast-paced environment, staying on top of industry trends, tools, and techniques to maintain a leading-edge approach.

Don't let a checklist hold you back - at Satispay, we thrive on diverse perspectives and unique strengths. Your individuality could be the missing piece to our puzzle! Even if you don't meet every skill listed above, we encourage you to apply if you're passionate about the role and believe you can contribute to our team's success.

Your Perks as a Satisperson
🙆🏻 Join an international team to grow with
🏡 Hybrid working policy
🍽️ Fuel your day with our meal vouchers
🌐 Preply language platform access to expand your language skills
⭐ Benefit from our 1.2k company welfare budget
🚀 Own part of Satispay’s success with our Stock Option Plan
👩🏻‍💻 Gear up with our tech equipment
🥳 Join us in the fun with team-building events, parties, trips, and more!

Our selection process is tailored to each role and includes at least a call with our Talent Acquisition Team, a technical evaluation, and a final in-person meeting. Your recruiter will share more insights during your first meeting with us!

Equal Opportunity Employer
At Satispay, we're proud to be an equal opportunity employer. We celebrate diversity and inclusion, welcoming individuals of all backgrounds. This opportunity is open to everyone, regardless - for instance - of race, color, religion, sex, gender identity, sexual orientation, and national origin. Join us in a workplace where everyone belongs!

Learn More About Us
Curious about our core values? Explore them here.

#LI-Hybrid

#LI-GA1

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Average salary estimate

$80000 / YEARLY (est.)
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$70000K
$90000K

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What You Should Know About Senior Data Scientist, Satispay

At Satispay in Milan, we're on a mission to transform the way people engage with payments. Joining us as a Senior Data Scientist means you’ll play a pivotal role in driving fintech innovation through your expertise in data science. Picture yourself developing predictive models and formulating data-driven solutions that directly impact our products and enhance business outcomes. You’ll find yourself collaborating with cross-functional teams to integrate machine learning models into our systems, helping us to stay at the forefront of revolutionized payment solutions in Europe. Key tasks include analyzing datasets to reveal actionable insights that help influence product design, designing systems for fraud prevention and credit risk management, and ensuring that our analytics pipelines run smoothly in production. We’re looking for someone who not only has a solid background in data science and fintech—ideally with at least three years of experience—but also brings technical savvy with Python, R, and various machine learning libraries. Your ability to communicate complex ideas simply will be crucial in fostering a data-driven culture within our organization. If you’re passionate about fintech and eager to keep learning in this ever-evolving landscape, Satispay is the place where your contributions will genuinely shape the future of financing. Here, we embrace diversity and allow your unique perspective to shine. Together, let’s create something truly remarkable as we pioneer a movement towards simpler, more accessible payment solutions!

Frequently Asked Questions (FAQs) for Senior Data Scientist Role at Satispay
What are the main responsibilities of the Senior Data Scientist at Satispay?

The Senior Data Scientist at Satispay is responsible for developing predictive models and data-driven solutions to optimize our product lines. This role includes analyzing datasets to uncover actionable insights, designing predictive systems for fraud and credit risk, and ensuring smooth integration of machine learning models into production. Additionally, collaboration with product managers and engineers to incorporate data science solutions into the Satispay ecosystem is a vital aspect of this position.

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What qualifications do I need to become a Senior Data Scientist at Satispay?

To qualify for the Senior Data Scientist role at Satispay, candidates typically need a Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. Experience of 3+ years in data science or analytics is essential, ideally within financial services, payments, or having a background in credit risk modeling. Proficiency in Python or R, along with experience in machine learning libraries and SQL, is also highly beneficial.

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How does Satispay support continuous learning for Senior Data Scientists?

At Satispay, we understand the importance of staying updated with the latest trends in fintech and data science. As a part of our team, you will have access to resources that encourage continuous learning, including our Preply language platform and a generous company welfare budget. We also promote a culture of innovation that rewards curiosity and the application of new techniques to enhance our services.

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What is the working environment like for a Senior Data Scientist at Satispay?

Satispay offers a hybrid working policy that blends the flexibility of remote work with the benefits of in-person collaboration. Our team culture is vibrant and inclusive, which is reflected in our team-building events and social activities. As a Senior Data Scientist, you’ll work in a dynamic, supportive environment surrounded by innovative thinkers who are as passionate about simplifying payments as you are.

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What opportunities for growth exist for a Senior Data Scientist at Satispay?

Satispay is firmly committed to the professional growth of its employees. As a Senior Data Scientist, you will not only sharpen your technical skills by working on critical projects, but you’ll also have opportunities to take on new challenges, mentor junior staff, and potentially move into leadership positions within the data science domain or other areas of the company.

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Common Interview Questions for Senior Data Scientist
Can you describe your experience with predictive modeling?

When answering this question, provide specific examples of predictive modeling projects you've worked on, detailing the techniques used, the problems you aimed to solve, and the outcomes achieved. Highlight your familiarity with tools like Scikit-learn or TensorFlow and discuss any relevant performance metrics.

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How do you handle missing or inconsistent data in your analysis?

It's important to discuss your approach to data preprocessing. Start by mentioning different techniques such as imputation or removing incomplete records. Emphasize the importance of understanding the context behind missing data and how these decisions can impact your model's effectiveness.

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What machine learning algorithms are you most familiar with, and how do you decide which to use?

Concisely explain the machine learning algorithms you are proficient in. Discuss factors like the type of problem (classification, regression), the nature of the data, and the business objectives that inform your choice. It’s beneficial to illustrate this with a practical example where you've applied these algorithms effectively.

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How do you stay updated with the latest industry trends in data science and fintech?

Talk about your commitment to continuous learning by mentioning sources you follow, such as academic journals, webinars, and online courses. You might also refer to active participation in relevant online communities or conferences that help you connect with other professionals.

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Describe a time you had to present complex data insights to a non-technical audience.

Use the STAR method (Situation, Task, Action, Result) to explain the scenario. Focus on how you distilled complex information into easily understandable points and the communication strategies you used, which could include visuals or storytelling.

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What role do you think data scientists play in transforming business decisions?

Discuss the importance of data-driven decision-making and how data scientists act as crucial facilitators in extracting insights from data that can inform and influence business strategies. Share your thoughts on the balance between technical analysis and business acumen.

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How do you validate the effectiveness of your machine learning models?

Explain the importance of model validation techniques, such as cross-validation, to ensure accuracy and generalizability. You could mention the metrics you rely on, like AUC-ROC for classification tasks or RMSE for regression, and how to interpret these results in business terms.

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Can you provide an example of a project where you improved a product or service using data analysis?

This is a great opportunity to showcase your analytical skills in practice. Highlight the project specifics, the analysis you performed, the insights you gathered, and how those insights led to quantifiable improvements in the product or service.

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What do you consider the most challenging aspect of working with large datasets?

Discuss challenges like data cleaning, ensuring data quality, and the need for efficient algorithms that can scale. Share strategies you’ve employed to manage and process large datasets, such as using distributed computing or optimized data pipelines.

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Why do you want to work as a Senior Data Scientist at Satispay?

Express your enthusiasm for the role by tying your skills and experiences to Satispay’s mission of transforming payment solutions. Mention specific aspects of Satispay's culture or innovations that excite you and reflect your values as a data scientist.

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Simplify payments to improve everyone’s life

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Full-time, hybrid
DATE POSTED
December 17, 2024

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