Top Remote Artificial Intelligence Data & Analytics Jobs

Own marketing channel performance tracking, reporting, experimentation, dashboards, forecasting, and LTV analysis. Develop measurement frameworks, identify data issues, and translate complex findings into actionable recommendations for Marketing, Growth, Product, and Finance stakeholders. The role requires strong SQL, BI dashboarding, marketing measurement, experimentation knowledge, and effective analytical communication, with AI tools used to accelerate reporting and analysis.

Analyzes and prepares customer data for successful migration to ServiceTitan. Works directly with customers to understand source databases, identify data issues, interpret database structures, and map data to ServiceTitan’s model. Writes queries to correct, reformat, and transfer data while coordinating with engineers, implementation teams, and onboarders. Manages shifting priorities, deadlines, project updates, and cross-functional communication to ensure accurate, timely data delivery.

Own an analytics project for go-to-market teams by combining CRM, campaign, and account data with SQL and Python. Build reusable data models, define acquisition and pipeline metrics, investigate data quality issues, add validation checks, and create dashboards and analyses. Communicate findings, recommendations, assumptions, and limitations to stakeholders while documenting reproducible workflows.

Own data ingestion, transformation, exchange, and integration workflows between K–12 Student Information Systems and Timely’s scheduling platform. Ensure pipeline accuracy, security, reliability, and scalability while collaborating with engineering, product, customer success, district IT teams, and SIS vendors. Develop documentation, process improvements, automation scripts, and lightweight Python tools; lead discovery for new SIS integrations and help scale the data integrations function.

Lead the architecture and delivery of end-to-end Azure data platforms, including ingestion, transformation, modeling, analytics, activation, APIs, and agentic AI integrations. Build production-grade batch and streaming pipelines using Microsoft Fabric, Azure Databricks, PySpark, Python, and SQL. Establish governance, security, lineage, and performance standards; troubleshoot critical systems; mentor engineers; advise client stakeholders; contribute to presales and reusable engineering frameworks.

Analyzes customer support, CX, survey, and operational data to produce reports, identify trends and gaps, and inform continuous-improvement roadmaps. Elicits and documents requirements, user stories, acceptance criteria, process maps, and alternatives analyses for IT and automation initiatives. Maintains CX roadmap and gap-analysis artifacts, prepares governance briefings, supports KPI reviews and UAT, and collaborates with technical, business, and government stakeholders.

Organize and curate large volumes of raw information: extract key points from transcripts, maintain clean spreadsheets, curate links/resources, tag and categorize content, and follow or propose systems for information structure. Part-time remote role with initial 10 hours/week and potential to grow.

Own business metadata and data governance activities across Finance, Commercial, HR, and Marketing. Partner with data stewards and domain owners to define, certify, map, validate, and publish business terms, metrics, KPIs, and data assets in Unity Catalog. Facilitate definition workshops, resolve terminology conflicts, improve Excel and Python intake processes, establish governance workflows, and document metadata lifecycle procedures.

Manage the health, performance, reliability, and cost of customer Snowflake and Databricks environments. Responsibilities include customer onboarding, account and warehouse setup, permissions, data ingestion, query optimization, cost reporting, incident response, escalation support, and automation using Python and Terraform. The role also advises customers and internal teams on data platform best practices and participates in on-call rotations.

Leads a mixed-methods research program on AI policy communications, overseeing survey and qualitative study design, fieldwork, analysis, vendor management, reporting, and documentation. Translates complex findings into executive-ready recommendations for Policy, Communications, Product, Marketing, Data Science, Legal, Privacy, and other stakeholders. Establishes rigorous research practices, reusable tools, benchmarks, and ethical standards while influencing senior cross-functional partners.