Who we are
Lightricks is a pioneer in innovative technology that leads to breakthrough moments throughout the creation process. With a mission to push the limits of technology to reimagine the way creators express themselves, we bring a unique blend of cutting-edge academic research and design to every user experience.
Our photo and video editing tools, including Facetune, Videoleap, and Photoleap, offer endless possibilities and inspiration, while our creator services, Popular Pays, provides content creators the ability to partner with brands to monetize their work and talents. We focus on putting creators in the center and empowering them from the moment inspiration strikes
The Data science team drives business and engagement optimization at Lightricks. We use machine learning and deep learning models to personalize our users' experience and optimize business KPIs. Our classification and recommendation systems allow us to provide better experiences for our users and carve Lightricks’ path to success.
What you will be doing
- Own machine learning and deep learning based projects: ideation, research, evaluation, production implementation and monitoring.
- Help solving complex diverse problems, and work with several stakeholders on a daily basis including product managers, developers, BI analysts and more.
- Build predictive machine learning models based on historical streams and usage data. For example, churn prediction and treatment optimization, product features recommendations and more
Your skills and experience
- 3+ years of experience as a data scientist in the industry. Experience from b2c companies is a plus.
- Strong background in machine learning, preferably in personalization related fields
- Familiarity with Deep Learning, NLP, Computer vision or Recommender systems - an advantage
- Hands-on experience with data science projects from research to production
- MSc or PhD in Computer Science, Data Science or a related field.
- Proficiency with Python and SQL
- Team player with excellent communication skills