Top Remote Data & Analytics Jobs in Boston, MA

Leads advanced analytics, reporting, scalable data models, dashboards, and data pipelines supporting Business and Marketing teams. Partners with senior stakeholders and AI Engineering to implement AI and machine learning workflows, predictive insights, and automation. Develops documentation, drives analytics engineering best practices, and mentors team members. Requires strong SQL, Python, APIs, data modeling, stakeholder communication, project leadership, and blockchain expertise.

Analyzes business performance, trends, competitor filings, and insurance product data for assigned states or product lines. Develops actionable recommendations, advanced queries, analytical tools, and strategic initiatives. Leads workstreams and low- to moderate-complexity projects, presents findings to product managers, supports countrywide implementations, and identifies improvements to property and specialty insurance offerings.

Build AI agents and data acquisition systems, evaluate dataset quality, define quality KPIs, and improve data processes. Partner with product teams to deploy data into customer-facing products and acquire datasets from third parties, including coordinating vendors and contracts. The role requires organizing multiple projects, structuring analyses, communicating tradeoffs, and using data to support investment decisions and customer outcomes.

The Data Scientist II will lead and execute health economic outcomes research projects, collaborate with stakeholders, and build analytical infrastructure while adhering to regulations.

Lead complex data analysis across Liftoff’s supply-side business, using optimized SQL on large-scale datasets and BI tools to build dashboards, reporting pipelines, and actionable insights. The role conducts root-cause analysis, evaluates experiments, translates technical developments into business impact, leads cross-functional initiatives, and mentors analysts. It partners with Engineering, Product, Data Science, Finance, Commercial teams, and executive leadership to influence roadmap and operational decisions.

Owns Pfizer GH&B’s AI-ready Snowflake data warehouse, data architecture, ontologies, governance, quality, lineage, access controls, and production reliability. The role supports AI/ML models, dashboards, and business-critical data applications; establishes testing, release, monitoring, and incident processes; directs contingent technical resources; and aligns business-specific data decisions with enterprise standards. Requires strong SQL, Python, Collibra, data warehousing, unstructured-data architecture, ontology, governance, and stakeholder-influence experience.

Analyzes autonomous-vehicle telemetry, time-series signals, incidents, software releases, and operational data to investigate safety issues and root causes. Integrates diverse data sources into analysis-ready datasets, validates data quality, applies engineering and signal-processing methods, and delivers rigorous findings for safety assurance and operational decisions. The role also develops reusable detection methods, metrics, pipelines, and analytical tooling while collaborating across engineering, operations, safety, human factors, and data teams.

Own Eve’s go-to-market data models and semantic layer for governed metrics including pipeline, conversion, CAC, win rate, ARR, and bookings. Establish certification frameworks, modeling standards, documentation, alerting, and analytical application patterns across the organization. Partner with Sales, Marketing, Customer Success, and RevOps stakeholders, resolve conflicting metric definitions, enable AI-grounded data tools, review contributions, and mentor analytics engineers.

Owns marketing and go-to-market analytics, KPI definitions, attribution, campaign and sales-play measurement, scoring-model evaluation, dashboards, and weekly leadership reporting. The role reconciles Salesforce, HubSpot, and attribution data; partners with data teams on source-of-truth datasets; and builds AI-powered analytics agents, automated reporting, anomaly alerts, and data-quality processes to guide budget and pipeline decisions.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.