A passionate data scientist with a desire to make a real-world impact is sought by a growing FinTech startup in San Francisco and Seattle! This individual will leverage their expertise to build innovative solutions that empower people to manage their finances.
The Role:
- This role offers the opportunity to join a dynamic Data Science team poised for significant growth.
- The successful candidate will collaborate closely with talented Data Scientists, Product Managers, and Engineers, translating data insights into impactful products.
- Their expertise in data science, deep learning, and neural networks will be harnessed to unlock the power of the company's rich datasets.
- They will develop and implement models that tackle critical business challenges, including fraud detection, risk management, and customer growth.
- Ultimately, this role plays a pivotal role in shaping the financial well-being of millions of people.
Qualifications:
- A Master's degree or PhD in a quantitative field (Statistics, Computer Science, Physics, Mathematics, Engineering) is required.
- The ideal candidate possesses 5+ years of hands-on experience in data science, deep learning, and neural networks.
- Proven experience with data engineering tasks (ETL processes) is a must.
- Proficiency in Python, R, or Scala is necessary.
- A keen mind for problem-solving and a relentless desire to learn are essential.
- Excellent communication and teamwork skills are crucial for success.
- A passion for building models and fostering a collaborative data science environment is desired.
Why Join This Company?
- Make a tangible difference in the financial future of millions.
- Thrive in a fast-paced, high-growth startup environment.
- Accelerate professional growth alongside experienced data scientists and machine learning engineers.
- Contribute to building best-in-class data models from the ground up.
- Work in a company prioritizing robust data infrastructure (available in San Francisco and Seattle).
Ready to embark on a mission-driven career? Apply today!
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