Top Machine Learning Jobs in Philadelphia, PA

The Senior Manager, Economic & Industry Insights, analyzes large datasets to generate actionable insights in the automotive sector, influences strategic decisions, and engages with stakeholders through published reports and presentations.

The Risk Analyst will develop strategies to mitigate fraud risk, analyze data, and collaborate with various teams to support low friction customer experiences. Responsibilities include reviewing accounts, creating analytical models, and reporting on progress against business goals.

The Manager of Decision Science will lead analytics efforts to enhance digital marketing, focusing on SEO and content metrics, utilizing statistical models and tools to drive business growth.

The Associate Director of Commercial Analytics & Insights will lead analytics for a business unit, develop strategies, perform analysis, and provide actionable insights for decision-makers in the pharmaceutical industry.

As a Senior Data Scientist, you will analyze data, build models, and collaborate with teams to enhance credit evaluation using machine learning.

The Statistical Programmer analyzes large datasets using SAS and SQL, and applies various statistical methods such as regression and multivariate analysis, while collaborating effectively with team members.

As a Business Operations Associate, you will analyze data to drive business growth, design A/B experiments, and optimize processes for user acquisition.

Join Clarity AI's Talent Community by submitting an open application for various roles in product, technology, finance, marketing, or operations to drive positive impact.

The Data Scientist I will analyze large datasets to extract insights, develop score models, forecast campaign performance, and monitor portfolio performance while collaborating with technology teams.

Lead delivery of data analytics for nonclinical safety: prioritize use cases, develop search/analysis/visualization solutions, implement statistical and ML models, and provide cross-functional scientific and data-science leadership.

Lead marketing data science efforts, overseeing analytics and machine learning strategies to enhance user acquisition, engagement, and retention. Mentor a team and communicate data insights to executives to influence marketing and budget decisions.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

The Staff Advanced Analyst will drive data analytics to improve CS Safety experiences, influence product decisions, and build measurement tools using data-driven insights.

The Business Analyst 2 analyzes AI-powered data solutions, optimizes customer experience automation, and collaborates with teams to drive business insights and value.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

As a P&C Actuary, you will assess risks for insurers, support audit teams, and maintain compliance with regulations, while growing client relationships and improving tools for efficiency.

Lead content programming through analysis, classification, and editorial judgment. Monitor performance, synthesize query analysis, propose product improvements, curate content, and collaborate with Engineering/Data Science on LLM/ML/NLP initiatives.

The VP of Data & Analytics is responsible for shaping data vision, driving analytics and AI integration, ensuring data governance, and leading a high-performing team to enhance educational outcomes.

The Manager, Growth Analytics & Marketing Science will build and evolve marketing measurement frameworks, drive analytics, and optimize marketing strategies through data and AI.

Lead RWE study design and execution: develop protocols, statistical analysis plans, and R/SQL programs to produce analysis-ready datasets, tables, and figures; apply causal inference, time-to-event, and predictive methods; collaborate with scientists and stakeholders to deliver RWE insights.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Join Nextdoor's machine learning team to build data-intensive products, develop ML models, analyze datasets, and enhance user experiences. Collaborate closely with product and data science teams.

Lead data acquisition and management strategies for AI models, analyze data systems, oversee partnerships, and guide a team in optimized data usage.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.