Data Scientist V – Ranking & Machine Learning

itD Tech•San Jose, CA

18h•Remote

About The Position

itD is seeking a Data Scientist V to drive data-driven improvements to machine learning ranking models that power content discovery and engagement. In this role, you will analyze large-scale datasets, develop predictive models, and generate insights that influence product features and user experiences across a major social media platform. The ideal candidate will bring deep experience in data science, statistical analysis, and machine learning, along with a track record of delivering predictive models, product experiment insights, and large-scale data analysis that improves recommendation systems and user engagement. Location: Remote within the United States. (Note: Contractors may be required to transition onsite if offices fully reopen.) We provide comprehensive medical benefits, a 401k plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship.

Requirements

10+ years of experience as a Data Scientist, including experience working with machine learning models.
Advanced proficiency in SQL and Python for large-scale data analysis and modeling.
Experience working with large datasets and performing exploratory data analysis.
Hands-on experience building machine learning models using frameworks such as PyTorch or TensorFlow.
Experience training or applying computer vision models.
Experience collaborating with cross-functional teams, including engineers and product stakeholders.
Master’s degree in Mathematics, Statistics, Computer Science, or a related technical field, or equivalent practical experience required.

Nice To Haves

PhD in a quantitative or technical discipline.
Experience working in social media or large-scale consumer technology platforms.
Experience developing predictive models for recommendation or ranking systems.
Strong background in product experimentation and A/B testing analysis.
PhD preferred.

Responsibilities

Analyze large-scale datasets to identify patterns, trends, and opportunities for improving ranking and recommendation models.
Develop predictive models and machine learning algorithms that enhance content recommendations and engagement signals.
Leverage computer vision techniques and feature extraction methods to evaluate image-based content and determine shareability signals.
Design and analyze product experiments, generating hypotheses and interpreting results to inform product improvements.
Collaborate with product engineers and cross-functional teams to translate analytical prototypes into scalable product features.
Investigate metric movements and performance trends for key recommendation and sharing products.
Create dashboards, visualizations, and leadership reports to communicate insights, experiment outcomes, and product performance.
Attend regular internal practice community meetings.
Collaborate with your itD practice team on industry thought leadership.
Complete client case studies and learning material (blogs, media material).
Build out material to contribute to the Digital Transformation practice.
Attend internal itD networking events (in person and virtual).
Work with leadership on career fast-track opportunities.