Design, develop, and maintain advanced analytics solutions, including predictive models and Generative AI applications, using SQL, Python, and modern AI and BI tools
Translate business problems into data-driven and AI-enabled solutions
Responsible for end-to-end delivery of analytics and AI initiatives, from data exploration and feature engineering to model development, deployment, and ongoing optimization
Design and engineer features from diverse data sources, including first-party and third-party data, to improve model accuracy and business relevance
Operationalize models using robust MLOps practices, including deployment pipelines, automated scoring, version control, and scalable data integrations
Define, monitor, and continuously improve model performance using appropriate metrics, including validation frameworks, drift detection, and retraining strategies
Translate model outputs into scalable, user-friendly analytics products and dashboards (e.g., segmentation, propensity scores, next best product recommendations) for end-user consumption
Design and evaluate experiments, including A B testing, to measure model effectiveness and quantify business impact
Integrate AI, machine learning, and Generative AI capabilities into analytics workflows and product solutions
Champion the adoption of Generative AI across teams by identifying and implementing use cases that improve productivity, insight generation, and client value
Explore and implement solutions leveraging LLMs, prompt engineering, and AI-assisted analytics
Educate and enable internal teams on AI and Generative AI best practices through documentation, training, and reusable frameworks
Collaborate with Product, Engineering, and Services teams to evolve the Analytics Edge and AI roadmap
Troubleshoot complex data, model, and system issues, identifying root causes and implementing scalable solutions
Communicate insights, risks, and progress clearly to stakeholders, including both technical and non-technical audiences
Create and maintain comprehensive technical documentation for data models, AI workflows, and processes
Participate in Agile and Scrum ceremonies and contribute to continuous improvement of team processes
Support client-facing discussions, demos, and training sessions as needed

Requirements

Bachelor’s degree in a relevant field or 5+ years of equivalent practical experience in data science, analytics, or applied AI
Strong expertise in SQL and Python for data analysis, modeling, and production workflows
Hands-on experience developing, deploying, and maintaining machine learning models in production environments
Experience with MLOps platforms and practices, including tools such as AWS SageMaker or similar
Experience working with modern data platforms such as Snowflake (preferred), Databricks, or BigQuery
Hands-on experience with Generative AI technologies, including LLMs, prompt engineering, and frameworks such as LangChain, as well as vector databases and related tooling
Proven experience applying AI and machine learning to real-world business or analytics problems with measurable impact
Experience with BI and data visualization tools such as Tableau or Power BI
Strong understanding of data warehousing, data modeling, and analytics architecture
Familiarity with cloud platforms, preferably AWS
Strong analytical thinking and problem-solving skills with attention to detail
Excellent communication skills, with the ability to convey complex concepts to both technical and non-technical audiences
Experience working in Agile or Scrum environments
Preferred Experience
Experience building or supporting AI-powered analytics products or features
Experience with Claude Code or Cortex code
Experience working with financial institutions (credit unions, banks)
Experience on a Product or innovation-focused team
Demonstrated curiosity and passion for emerging AI technologies

Benefits

A flexible remote work policy with optional access to our Portland, Maine office
A 4-day workweek after 3 years of service
Generous paid time off, including 11 holidays
Medical, disability, life insurance, and optional dental/vision
401(k) retirement plan with company match
Training & certification reimbursement
Milestone recognition programs, annual PTO increases, and more

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLPythonMLOpsmachine learningGenerative AIdata analysisdata modelingpredictive modelingfeature engineeringA/B testing

Soft Skills

analytical thinkingproblem-solvingcommunicationcollaborationattention to detailcuriositytrainingdocumentationstakeholder engagementcontinuous improvement