Data Science Researcher - Finance and Marketing

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 advanced statistical models, 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

As a data scientist in the Business Data Science team, you will be leading finance and marketing projects with focus on time series handling.

Lead machine learning based projects from business requirements, through research, evaluation, production implementation and monitoring.

Work on diverse problems and domains, and work with several stakeholders on a daily basis including finance and marketing managers, developers, BI analysts and more.

Build ML and statistical models based on historical revenue streams and usage data to predict different KPIs. For example, LTV, campaign’s ROI, user’s attribution and more.

Your skills and experience

3+ years of experience as a data scientist in the industry, experience from b2c companies is a plus.

High communication skills, understanding business needs, and combining the business case into the data science area in order to leverage decision making.

Deep understanding of classical ML & DL algos for a wide spectrum of problems and domains. Time series modeling - must.

MSc or PhD in Computer Science, Data Science, Statistics or a related field.

Proven hands-on experience developing and researching algorithms in various fields and data science/machine learning techniques such as: boosting algorithms, time series models, clustering, anomaly detection methods, and more.

Proven experience in taking projects through all the stages of a new ML model, from data analysis and labeling to prototyping, implementation in a production environment, and monitoring and maintenance. Delivery oriented.

Proficiency with Python and SQL.

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