Sr Data Scientist

1 week ago


Hyderabad Telangana India, Telangana DAZN India Full time

Is your next career move to work in a team which uses data, reporting and analytical skills to help answer business questions to make DAZN a data-driven company?

DAZN is a tech-first sport streaming platform that reaches millions of users every week. We are challenging a traditional industry and giving power back to the fans. Our new Hyderabad tech hub will be the engine that drives us forward to the future. We’re pushing boundaries and doing things no-one has done before. Here, you have the opportunity to make your mark and the power to make change happen - to make a difference for our customers. When you join DAZN you will work on projects that impact millions of lives thanks to your critical contributions to our global products

This is the perfect place to work if you are passionate about technology and want an opportunity to use your creativity to help grow and scale a global range of IT systems, Infrastructure, and IT Services. Our cutting-edge technology allows us to stream sports content to millions of concurrent viewers globally across multiple platforms and devices. DAZN’s Cloud based architecture unifies a range of technologies to deliver a seamless user experience and support a global user base and company infrastructure.

This role will be based in our brand-new Hyderabad office. Join us in India’s beautiful “City of Pearls” and bring your ambition to life. Considering the Urgency, we are only seeking Immediate Joiners

Job Title: Data Scientist

Location: Hyderabad

Work Mode: Work from Office.

Seeking Immediate Joiners only.

Job Summary:

We are seeking a passionate and experienced Data Scientist / Machine Learning Engineer with a strong foundation in Machine Learning, Deep Learning, and Generative AI (GenAI). The ideal candidate will have hands-on experience with modern AI frameworks and libraries, a proven ability to design, develop, and deploy scalable ML solutions, and expertise in working with Large Language Models (LLMs).

You will leverage your skills to drive impactful solutions, staying at the forefront of advancements in ML, DL, and GenAI. You will work on cutting-edge projects, incorporating the latest technologies into production-ready systems. If you are excited about advancing your career in a dynamic, innovation-driven environment, we invite you to join us

Key Responsibilities:

• Role Recommendation Engine, for Data accuracy-Develop, train, and fine-tune machine learning and deep learning models for diverse business use cases. With an Overall experience of (2-6 Years)

• Work with Generative AI and LLMs, including customizing, fine-tuning, and deploying models for real-world applications.

• Stay updated with the latest advancements in Machine Learning, Deep Learning, and Generative AI, and incorporate them into projects.

Required Skills:

• Machine Learning Frameworks: Proficiency in Scikit-learn, TensorFlow or PyTorch.

• Deep Learning: Experience building and training deep learning models, including CNNs, RNNs, Transformers, and other architectures.

• Generative AI: Hands-on experience with Generative AI models, including fine-tuning and deploying LLMs.

• Programming: Strong skills in Python; familiarity with libraries like NumPy, pandas, and Matplotlib.

• Data Handling: Experience working with structured and unstructured data, including text, images, and time-series.

Good to have Skills:

• Exposure to tools like Hugging Face Transformers for working with LLMs.

• Understanding of MLOps practices, including CI/CD pipelines for ML models.

• Experience with GPU-accelerated computing.

• Experience with distributed training frameworks (e.g., Horovod, PyTorch Lightning).

• Cloud Platforms: Familiarity with cloud services like AWS

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.

• 3 - 6+ years of professional experience in Machine Learning and Deep Learning.

• Proven track record of deploying ML/DL models in production environments.


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