Top AI & Machine Learning Jobs

Leads the full analytics lifecycle for advertising sales, including data preparation, exploratory analysis, predictive modeling, validation, productionalization, interpretation, and recommendations. Develops scalable data-driven solutions using statistical and machine learning methods, presents findings to varied audiences, mentors junior staff, contributes to strategic direction, and manages project execution. Requires advanced programming, SQL, cloud, big-data, forecasting, optimization, and AI/ML expertise.

Leads the full analytics lifecycle for Spectrum Reach’s advertising sales business, including data preparation, exploratory analysis, predictive modeling, validation, productionization, forecasting, and interpretation. Develops scalable analytics products, synthesizes recommendations, presents findings to diverse audiences, manages project execution, and mentors junior data professionals. Requires advanced statistical, machine learning, programming, cloud, and big-data expertise.

Lead AI product strategy and roadmap for Spectrum News. Translate editorial and business needs into product requirements, collaborate across teams, guide development of personalization, recommendations, discovery, and newsroom productivity AI features, ensure responsible AI governance, measure impact with analytics, and communicate vision to stakeholders.

Paid, full-time 11-week data science internship supporting service reliability and customer experience initiatives. Responsibilities may include exploring data, building models, writing and deploying code, and visualizing insights with Tableau. Interns also participate in professional development, networking, mentorship, community service, and cross-functional projects. The role requires current bachelor’s enrollment, a minimum 3.0 GPA, graduation between December 2027 and May 2028, U.S. work authorization without sponsorship, and local travel to internship events.

Leads AI-enabled HR initiatives across recruiting, onboarding, talent management, and employee experience. Designs experiments, metrics, data pipelines, and feature sets for AI capabilities such as talent matching and case deflection. Monitors model performance, fairness, privacy, security, drift, and adoption while partnering with HR, Legal, IT, and vendors. Evaluates build-versus-buy opportunities and maintains documentation supporting transparency and reproducibility.

Leads data science for an AI-native behavioral intelligence platform, building predictive audience, identity, measurement, and partner models at household scale. Owns feature stores, causal measurement, embedding model strategy, MLOps, responsible AI, privacy standards, and commercial validation. Builds and manages a data science organization, partners with technology, product, sales, legal, and customers, and converts technical evaluations into marketable products and contracts.

Supports the end-to-end data science lifecycle, including ETL, data cleaning, statistical analysis, model development, validation, deployment, and post-launch measurement. Collaborates with cross-functional stakeholders to identify business opportunities, improve data quality, connect data sources, and communicate insights. Develops models using Python and machine learning techniques such as Logistic Regression, Random Forest, and XGBoost while presenting recommendations to business leaders.

Develops end-to-end data science solutions, including ETL, statistical and machine learning model development, validation, deployment, and impact measurement. Collaborates with cross-functional teams to implement production models, improve data quality, identify correlations, and communicate insights to business stakeholders. Requires Python, SQL, analytical modeling, and familiarity with Spark and Hive.

Paid, full-time 11-week data science internship supporting accessibility initiatives. The intern will clean and document datasets, analyze census and ACS disability data, map geographic insights, evaluate assistive technology feature usage, build dashboards, compare external and internal data, and present findings and recommendations. The role also includes professional development, mentorship, networking, and local travel to intern events.