Data Scientist (NLP Deep Learning Engineer)

About the Job:
The company is on a mission to provide people with enhanced visibility, control, and freedom over their finances. Since its inception in 2015, the company has grown rapidly, now serving over 65 million customers with a range of products that enable better management of money, from spending and saving to investing and exchanging.

The Data Science team at the company is tasked with solving complex problems and improving customer experiences. As a Deep Learning Engineer, you will work on integrating GenAI and large language models (LLMs) to build transformative products, including user-facing tools and advanced process optimizations.

Key Responsibilities:

• Build AI-driven features from scratch, such as personal assistants, chatbots, and copilots.
• Develop user-focused and backend features using deep learning.
• Deliver impactful, scalable, data-driven AI solutions.
• Collaborate with Product, Engineering, and Data teams to tackle deep learning challenges.
• Integrate cutting-edge AI technologies to foster innovation at the company.

What You'll Need:

• Experience in deep learning within the natural language processing area and LLMs.
• A bachelor's degree in a STEM field (mathematics, computer science, engineering).
• Excellent knowledge of data science tools, particularly Python and SQL.
• A strong understanding of probability and statistics fundamentals.
• Big-picture thinking for diagnosing problems and productionizing research.
• Excellent communication and collaboration skills with Product Owners and business heads.

Nice to Have:

• A master's or PhD in a quantitative discipline.
• Proficiency in additional programming languages like Java, Scala, or C++.
• Experience working at a large tech company with a valuation of over $15 billion.
• Participation in school/university competitions in physics, math, economics, or programming.

The company is committed to creating an inclusive workplace and encourages applications from individuals with diverse backgrounds and experiences.

Language Requirements: Not specified.