CRED is Hiring Data Scientists
Fintech firm CRED is expanding its AI and machine learning capabilities and is seeking two data scientists to join its team. For professionals with a passion for LLMs, generative AI, and deep learning, this could be the right opportunity to work on solutions that redefine financial intelligence. At CRED, data scientists experiment and innovate in an environment that fosters research and real-world applications. From predictive modelling to scalable AI architectures, the role offers a mix of challenges. They will work on developing and deploying AI-driven solutions, collaborate with cross-functional teams, and implement real-time models that push the boundaries of automation. There’s also an opportunity to publish research and present at industry conferences, ensuring data scientists stay ahead in the rapidly evolving fields of machine learning and AI. CRED is looking for professionals with more than three years of experience in data science, particularly in NLP and deep learning. Strong programming skills in Python, Java, or Scala are preferred, along with hands-on experience in building scalable AI/ML solutions. Expertise in working with LLMs and generative AI would also be favoured. According to the fintech platform, CRED’s work culture is built on trust. There are no rigid job titles or fixed work hours. Moreover, productivity at the company is measured by impact, not time spent at a desk. Employees even receive their salaries before their official joining date, a strong statement of trust that defines CRED’s ethos. The company also claims to ensure a stress-free environment, offering a comprehensive health insurance plan, paid sick leaves, and an in-house pantry offering free lunch and dinner for all team members. It’s a workplace that values well-being just as much as innovation.
At CRED, data scientists experiment and innovate in an environment that fosters research and real-world applications.
CRED is looking for professionals with more than three years of experience in data science, particularly in NLP and deep learning.
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