Television Content Analytics Pte Ltd, TVConal, is a technology startup in Singapore with the main line of business in media content creation and sports analytics. The R&D department in TVConal is a unique research group that strives to drive best practices and innovation across all televised professional sports. The primary focus for this fast-paced and collaborative department is on analytics, data strategy, and second screen applications.

TVConal is driven by the passion for solving the most challenging problems in the television industry on viewer engagement. The progressing digitization of television viewing activities has revolutionized television industry. At TVConal we provide a foundation for building automation in a deeper and more compelling content generation by gaining insights into viewers’ behaviour and preferences. Our mission is to let sports viewers enjoy watching a game in the depth they desire.

TVConal supplies the technological resources and solutions that enables broadcasters, media, and entertainment companies to deliver more engaging content and better identify and seize new opportunities. We assist our clients in evaluating the way a program or a show is received or providing insights about interests for a new one. Our services include consulting, analyzing, and data visualization.

Motivated candidates with in-depth machine learning, artificial intelligence, deep learning, or pattern recognition knowledge, are particularly encouraged to apply. You will be involved in creating cutting-edge technologies that can significantly enhance the way professional sports are played and watched. In this role you will develop and implement statistical and machine learning models for analyzing and predicting the outcome of sporting events. These models are used in applications for better viewing of sports events and for fan engagement. You should be excited by intellectual challenges and confident enough to contribute ideas to the team. You will be able to demonstrate your abilities through tangible projects assignments. Technical Requirements  Degree in computer science or equivalent  Strong algorithmic and programming skills  Expertise in developing deep learning algorithms, various classification and regression models, clustering, temporal, and Bayesian models  Solid background in parsing, debugging, optimizing existing codes  Familiarity with deep learning platforms, architectures, and regularizations techniques is a must  Knowledge of web scraping is a plus  Experience in integrating machine learning with real-time computing including mobile apps is a plus