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We are proud to present you with the following opportunity.

About Our Client:

Frenzy AI is an innovative company revolutionizing the e-commerce landscape through the power of artificial intelligence. By leveraging cutting-edge machine learning technologies, they create personalized shopping experiences that drive user engagement and business growth. Frenzy AI fosters a culture of innovation, collaboration, and impact, offering a dynamic environment for professionals who want to shape the future of e-commerce.

Role Overview:

As a Data Scientist at Frenzy AI, you will play a crucial role in building and deploying scalable recommendation systems that enhance user experience and business outcomes. You will collaborate closely with cross-functional teams to develop machine learning models, perform data analysis, and optimize personalization strategies. This is an exciting opportunity to work with large-scale datasets and deploy models that make a real impact.

Responsibilities:

Develop, implement, and deploy recommendation systems using techniques like matrix factorization, deep learning, and implicit/explicit feedback models
Perform data analysis and build predictive models leveraging behavioral data and trend signals
Work with large-scale data pipelines and contribute to the development of A/B testing frameworks
Collaborate with product and engineering teams to design and optimize personalization and user segmentation strategies
Analyze and interpret data to deliver actionable insights that drive product ranking and user engagement
Communicate technical findings effectively to non-technical stakeholders
Continuously research and apply state-of-the-art machine learning techniques to enhance recommendation performance

Requirements

3+ years of experience in data science, ideally in e-commerce or consumer-tech environments
Strong proficiency in Python and machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, and LightFM
Hands-on experience building and deploying recommendation systems (e.g., matrix factorization, deep learning-based recommenders, implicit/explicit feedback models)
Experience with SQL, Pandas, and Jupyter for data analysis
Strong understanding of product ranking models using behavioral data
Experience working with large-scale data pipelines and A/B testing frameworks
Excellent problem-solving skills and ability to communicate complex technical concepts clearly

Benefits