Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global media and entertainment organization operates a broad portfolio of iconic content, entertainment brands, and digital streaming services. Its teams bring together creative talent, technology innovators, researchers, and engineers to develop engaging experiences and build the next generation of digital entertainment products.
The organization provides opportunities for professionals to work on large-scale technology initiatives involving artificial intelligence, machine learning, data science, content personalization, and digital media.
The Principal Research Scientist (Recommender Systems) will lead large and complex technical initiatives focused on developing innovative machine learning algorithms and scalable AI solutions. The role will direct the work of Machine Learning and Artificial Intelligence researchers and engineers while advancing personalization, recommender systems, and search capabilities designed to improve user experience and support business growth.
The successful candidate will work closely with product, engineering, content, marketing, and research stakeholders to identify machine learning opportunities, accelerate AI innovation, and deliver measurable business impact.
Key Responsibilities
- Develop innovative data science solutions using machine learning, deep learning, statistical modeling, and quantitative modeling techniques.
- Lead and mentor Machine Learning and Artificial Intelligence researchers and engineers.
- Introduce modern machine learning approaches, technologies, and development processes.
- Partner with ML engineering leadership to design and develop scalable machine learning systems.
- Identify data science opportunities that can generate meaningful business value.
- Define key areas of the ML and AI roadmap and support successful implementation.
- Educate internal and external stakeholders on machine learning strategies, capabilities, and results.
- Provide thought leadership for ML and AI applications across personalization, recommender systems, and search.
- Develop and promote best practices for scoping, building, validating, deploying, and monitoring ML and AI products.
- Prepare and present machine learning modeling results and analytical insights to senior leadership.
- Drive technical projects from research and experimentation through scalable production implementation.
- Collaborate effectively with cross-functional teams to establish trusted partnerships and deliver impactful solutions.
Required Qualifications
- Master’s degree in Computer Science, Mathematics, Physics, Engineering, Statistics, Operations Research, or another equivalent quantitative field. A PhD is preferred.
- 8+ years of professional experience in Machine Learning, Artificial Intelligence, and Data Science.
- Proven track record of driving technical innovation and delivering measurable business impact.
- Strong experience with recommender systems, personalization systems, collaborative filtering, and information retrieval systems.
- Advanced expertise in machine learning, deep learning, and statistical modeling.
- Experience with techniques such as causal inference, ensemble methods, neural networks, natural language processing, reinforcement learning, and bandit algorithms.
- Familiarity with modern large language model-based techniques for recommender systems and personalization.
- Advanced SQL skills and experience working with large-scale data platforms.
- Experience with cloud and big data technologies such as AWS, Snowflake, Spark, or Google Cloud.
- Proficiency in machine learning and deep learning programming languages and platforms, including Python, TensorFlow, Keras, or PyTorch.
- Experience deploying machine learning algorithms and advanced modeling solutions into production environments.
- Ability to deliver results effectively in a fast-paced and high-energy environment.
- Strong communication skills, including the ability to explain complex analytical concepts and algorithms to non-technical audiences.
- Demonstrated ability to work effectively with cross-functional teams and build strong stakeholder relationships.
- Experience in the digital media and entertainment industry is preferred.
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