Top Remote Data Science Jobs in Portland, ME

This role involves leading data science projects, designing technical solutions, implementing machine learning methodologies, and developing data workflows for cybersecurity applications.

The Data Scientist II will develop machine learning algorithms, architect data solutions, and support cybersecurity initiatives by analyzing complex data sets.

Lead advanced analytics and ML for partner-facing teams: build end-to-end predictive models (churn, lead scoring, health scores), marketing attribution and mix models, and maintain ML lifecycle standards. Develop agentic workflows and Claude Skills to accelerate work, mentor analytics team, and translate model outputs into actionable insights for Sales, Marketing, and CX.

Develop and validate SDTM and ADaM datasets using R per CDISC standards, support TLF generation in R or SAS, perform QC and reconciliation, collaborate with biostatistics and clinical teams, contribute to automation, documentation, and version control for regulatory-compliant clinical trial deliverables.

Design, implement, and evaluate advanced NLP/NLU systems for clinical text using transformer and research-oriented neural architectures. Prepare and enrich clinical datasets, run experiments and error analyses, mitigate model risks (bias, drift, hallucination), and partner with ML engineers to deploy models into a compliant cloud environment.

Lead analytic efforts for Humana In-Home Programs: build member-level predictive models, forecasting, segmentation, and impact evaluations to improve engagement, close care gaps, and support HEDIS Stars performance. Partner with business, ops, and tech teams to deploy cloud-based ML solutions and present insights to senior leaders.

The Senior Data Scientist will design and deploy machine learning models, analyze complex datasets, develop analytical solutions, and mentor junior team members in a remote environment.

Lead retention and churn efforts by building survival and lifecycle-state models, classifying churn reasons, creating personalized win-back and next-best-action interventions, optimizing offers/promos, designing uplift experiments, and owning production model lifecycle, monitoring, and MLOps across Product, CRM, Marketing, and Engineering.

Lead Data Scientist responsible for creating ML-driven risk assessments and AI workflows within a SaaS security platform, ensuring effective decision-making and system reliability.

Lead development of digital twin and simulation models for warehouse operations, deploy AI-driven decision systems, build forecasting and optimization models, validate experiments linking operational metrics to financial impact, and partner with engineers, operations, and external AI/academic partners to scale innovations across fulfillment networks.

The Sr. Data Scientist will design, develop, and deploy AI models and tools, mentor teams, and drive data-driven insights while collaborating with cross-functional teams.

The Senior Data Scientist leads data-driven initiatives, optimizing analytics for business decisions, mentoring staff, and ensuring data quality across healthcare projects.

The Principal Data Scientist will design, develop, and deploy machine learning models, innovating methodologies and collaborating across teams to enhance financial decision-making and risk management.

As a Principal Data Scientist, you'll design and deploy cutting-edge machine learning models to drive financial success for customers and guide technical teams.

As a Lead Data Scientist, you will shape data strategy, develop predictive models, analyze healthcare datasets, and collaborate with teams to enhance MDCalc's clinical decision tools.

As a Senior Data Scientist, you will identify business opportunities, build machine learning solutions, partner cross-functionally, and translate analyses into actionable insights.

Build, deploy, monitor, and document predictive models and analytical reports; translate findings for non-technical stakeholders; ensure model quality, fairness, and explainability; collaborate with data engineers and train staff on data literacy; support production ML infrastructure on AWS.

Lead AI/ML initiatives at Risepoint to develop predictive models for enhancing student engagement and retention, coordinating cross-functional teams to achieve measurable outcomes.

Lead development of graph-based identity resolution for CTV advertising: design models and validation, analyze large identity datasets with distributed tools, productionize data-science workflows, partner with engineering/product, and apply privacy-by-design while leveraging LLMs and AI-assisted development.

The Geospatial Scientist leads data management initiatives, oversees data governance, and ensures quality and compliance of geospatial data for DHS.

The role involves developing NLP systems for medical document analysis using advanced deep learning techniques, collaborating with domain experts, and deploying models in a healthcare setting.

Design and validate clinical and biomarker data pipelines, perform source-to-target mappings (e.g., EHR to data model), extend ontologies and vocabularies, ensure data quality, evaluate informatics tools, and support data architecture and analysis workflows for a regulatory-grade platform.

The Senior Data Scientist will analyze customer data, design experiments, build models, and support data-driven decision-making across product, marketing, and customer experience teams.

Embed with a core business unit to define problems, build metrics, run analyses and experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

Embed with a core business area to define problems, build metrics, run analyses and experiments, produce insights and recommendations, and drive end-to-end execution to improve product, growth, AI/automation, or partnerships.