Top Senior Data Science Jobs in Portland, ME

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.

Design, develop, and deploy time-series and machine-learning forecasting models (ARIMA, SARIMA, ETS, XGBoost, LightGBM) for demand planning, inventory, and sales forecasting. Perform large-scale SQL data processing, operationalize models in cloud environments (Azure preferred), present insights, and lead client workshops.

Lead development, validation, and monitoring of predictive models and AI solutions for pricing, underwriting, claims forecasting, and clinical review. Apply feature engineering, time-series forecasting, and machine learning to produce production-ready code, mentor junior staff, and translate model outputs into actionable business recommendations while ensuring model governance and compliance.

As a Principal Data Scientist, you'll drive data-driven strategies across Growth and Membership Operations, integrating AI tools and managing complex data systems to enhance operational performance.

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

The Principal Data Scientist Consultant will develop and maintain clinical datasets using R, ensure CDISC compliance, generate reports, and contribute to internal tools while collaborating with clinical teams.

As a Senior Data Scientist, you'll lead projects leveraging data to enhance healthcare outcomes, mentor team members, and align data efforts with business goals.

As a Senior Data Scientist, you will develop statistical models and machine learning algorithms to improve patient enrollment and trial management while ensuring compliance in a healthcare data environment.

As a Senior Data Scientist, you will design and deploy machine learning and graph algorithms to enhance identity trust solutions, own end-to-end projects, and collaborate with product and engineering teams to improve KYC and compliance products.

The Principal Data Scientist will lead measurement strategy for Zillow's advertising business, focusing on ad performance, experimentation, and data-driven decision-making to drive revenue growth and advertiser value.

Lead the design and deployment of machine learning and graph-based systems for international identity verification, ensuring compliance and addressing regional challenges.

The Senior Data Scientist will design ML-based entity resolution systems, build and refine NLP and ML models, and translate model results into business impact while supporting data strategy and improving data pipelines.

The Senior Data Scientist in Conversational AI & NLU designs and optimizes AI solutions, evaluates models, collaborates with stakeholders, and analyzes conversational data to improve user experience.

Lead the development and deployment of advanced ML/AI products, mentoring teams and collaborating with stakeholders to influence business outcomes.

The Senior Manager, Data Science & Analytics will lead a team to drive analytics and experimentation strategies for Yahoo Mail's growth and monetization, engaging with product, finance, and marketing to transform data insights into actionable strategies for success.

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 at Fetch will develop and scale data science capabilities, architect predictive models, and influence product strategy through collaboration and experimentation. They will lead initiatives focused on engagement, churn, and business impact measurement using advanced analytics and machine learning tools.

The Senior Data Scientist will develop machine learning models, conduct A/B tests, and work with behavioral data to enhance customer engagement and partner ROI.

Lead data science for Yahoo Mail subscriptions: analyze acquisition, conversion, pricing, retention, and churn; design and analyze A/B and multivariate experiments; build predictive and clustering models; partner with product, engineering, design, and business teams to deliver data-driven growth and monetization insights.

Develop and prototype learning-based models using data-centric techniques; design and maintain multi-modal data and feature extraction pipelines; build auto-labeling systems; perform ETL and optimize SQL for analysis/ingestion; collaborate with data infrastructure and ML engineers to integrate workflows; write maintainable code and participate in code reviews to support scalable ML production.

Seeking a Senior Data Scientist to lead predictive analytics and machine learning initiatives. Responsibilities include building ML models, data management, and mentoring junior data scientists. Must have expertise in AWS and strong statistical knowledge.

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.

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.

Lead development and operationalization of measurement products (MMM, incrementality, insights, recommendations). Build, deploy, and maintain production-grade statistical and ML systems, debug end-to-end data and model issues, evaluate methodologies, and partner with engineering, product, and customer teams to improve measurement accuracy and reliability. Provide customer-facing explanations and support for measurement outputs.

Build and deploy credit and fraud risk models using advanced ML/statistical methods. Partner with stakeholders, extract insights from large transaction datasets, automate feature/production pipelines, mentor junior data scientists, and ensure model quality and deployment scalability.