Top Entry Level Data & Analytics Jobs in Portland, ME

Evaluate AI-generated responses using a personal Gmail account and email history in English and Korean. Assess relevance, accuracy, helpfulness, personalization, and unsupported assumptions; compare responses and provide detailed feedback. Maintain privacy and confidentiality while working independently remotely. Requires a mixed-language inbox, approximately 1,000+ emails, reliable computer and internet access, at least four hours daily availability, and four hours of PST overlap for a 16-week contract.

Reviews and annotates Japanese-language text and images to help train AI systems. Responsibilities include drawing bounding boxes, answering structured questions, writing short summaries, and following annotation guidelines. This is a fully remote, long-term role requiring native or fluent Japanese, strong reading comprehension, basic computer skills, attention to detail, and reliable adherence to instructions. No prior experience is required; training and a language assessment are provided.

Evaluate AI-generated responses for relevance, accuracy, helpfulness, and personalization using a professional Google Workspace account and business email history. Compare responses, identify unsupported assumptions or personalization issues, provide detailed feedback, follow evaluation guidelines, and maintain confidentiality. Requires native German proficiency, an established business Gmail inbox, analytical attention to detail, independent remote work, and availability of up to 40 hours weekly with PST overlap.

Enters, verifies, updates, and organizes information across databases, spreadsheets, and internal systems. The role identifies discrepancies, flags incomplete records, runs basic reports, maintains confidentiality, and documents recurring issues. Success is measured by accuracy, productivity, and turnaround time. Candidates need strong attention to detail, accurate typing, spreadsheet proficiency, basic computer skills, and the ability to perform repetitive work consistently.

Create and validate complex datasets for AI benchmark tasks, including files with malformed records, missing data, truncations, and inconsistent formatting. Define correct final states, write detailed grading rubrics, and assess AI outputs for accuracy and completeness. The role requires exceptional attention to detail, error detection, format reconciliation, accurate documentation, and clear asynchronous communication in regulated or audit-sensitive contexts.

Build and scale distributed data pipelines and architectures supporting AI products and research. Responsibilities include processing large datasets with Spark, designing AWS data systems, managing SQL and NoSQL storage, writing Python and SQL, ensuring data quality and reliability, and implementing automation, orchestration, monitoring, and scalable data operations.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Build and maintain Snowflake and dbt data models using medallion architecture, CDC ingestion, star schemas, and slowly changing dimensions. Develop governed semantic datasets for BI and AI workloads, implement testing, documentation, monitoring, alerting, row-level security, and performance tuning. Partner with product and business stakeholders to translate reporting needs into reliable multi-tenant SaaS data solutions.

Investigate and resolve data integration, file processing, and transfer issues. Monitor automated jobs, use SQL and SSIS to validate data, manage SFTP workflows, reprocess files, document integration processes, and collaborate with internal teams to ensure accurate and reliable client and vendor data exchanges.

Contributes to building and optimizing a large-scale data lake and reliable data pipelines for cybersecurity analytics. Responsibilities include data modeling, distributed processing, workload optimization, monitoring, observability, CI/CD, code reviews, and supporting MLOps. The role collaborates with senior engineers to improve processes and deliver cost-effective cloud data solutions.

Maintains accurate CRM data across HubSpot and ServiceNow by processing data requests, entering and cleaning records, resolving duplicates, managing account relationships, supporting bulk uploads, and addressing cross-system data issues. Partners with Sales, Marketing, and IT Development to ensure accurate integrations, workflows, deal data, and adherence to data processes.

Research and monitor political news, government sources, candidates, officeholders, and elections. Update Ballotpedia articles and databases, verify data accuracy, conduct jurisdictional research, write and proofread neutral content, maintain tracking spreadsheets, and collaborate across teams. The role requires strong political knowledge, organization, communication, project management, attention to detail, and flexibility for occasional evening and weekend work.

Manages HR data, analytics, reporting, dashboards, pipelines, integrations, and automation. Supports compensation, performance management, workforce planning, HRIS maintenance, and employee listening initiatives. Builds data models and AI integrations, audits data integrity, develops actionable insights, and presents findings to HR and executive leadership. Requires strong compensation expertise, advanced Excel, HRIS and BI experience, scripting, data modeling, and handling confidential information.

Leads Citizens’ enterprise semantic analytics strategy and AtScale-based semantic layer operating model. Establishes governed, auditable processes for requirements, metric definitions, modeling, validation, certification, deployment, and change management. Oversees BI platform strategy across Power BI, Tableau, Alteryx, and WebFOCUS, while driving natural language query capabilities, business adoption, partner delivery, executive governance, and distributed team leadership.