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Weekend Data Analyst Jobs in Portland, ME (NOW HIRING)

Master Data Analyst Location: : Scarborough, Maine Duration: 12 Months - 100% Onsite role. Skills Looking For: * Data Management experience; SAP experience * Creating new parts in SAP (Part number ...

Business Analyst

Portland, ME · On-site

$85K - $100K/yr

Analyze current-state processes, workflows, and data structures; develop future-state designs that improve efficiency, clarity, and standardization. * Support software selection efforts including RFP ...

Analyze current-state processes, workflows, and data structures; develop future-state designs that improve efficiency, clarity, and standardization. * Support software selection efforts including RFP ...

Analyze current-state processes, workflows, and data structures; develop future-state designs that improve efficiency, clarity, and standardization. * Support software selection efforts including RFP ...

Business Analyst

Portland, ME · On-site

$60 - $90K/hr

Collaborate with the Business Intelligence team to analyze data, identify trends, and provide actionable insights to support decision-making. * Utilize BA tools (e.g., Azure DevOps, Visio, Excel) to ...

Business Analyst

Auburn, ME · Hybrid

$55K - $90K/yr

The Business Analyst provides support to the Product Owners, the Technology Team as well as the greater organization. They ensure the timely discovery, development, testing and delivery of items ...

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Weekend Data Analyst information

See Portland, ME salary details

$34.8K

$84.5K

$139.1K

How much do weekend data analyst jobs pay per year?

As of Jul 27, 2026, the average yearly pay for weekend data analyst in Portland, ME is $84,550.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,900.00 and $99,200.00 per year, depending on experience, location, and employer.

What is the difference between Weekend Data Analyst vs Part-Time Data Analyst?

AspectWeekend Data AnalystPart-Time Data Analyst
CredentialsBachelor's in Data Science, Statistics, or related field; often some experienceSimilar credentials; may require less experience or specific certifications
Work EnvironmentTypically on-site or remote, working during weekends or specific hoursFlexible hours, can work weekdays or weekends, often remote
Employer & IndustryBusinesses needing weekend analysis, retail, healthcare, or financeVarious industries, including retail, marketing, and consulting
Search & Comparison IntentLooking for weekend-specific data rolesSeeking flexible or part-time data analysis jobs

The Weekend Data Analyst and Part-Time Data Analyst roles share similar credentials and work environments but differ mainly in scheduling. Weekend Data Analysts focus on weekend-specific hours, often for businesses needing weekend support, while Part-Time Data Analysts have flexible hours across the week. Both roles suit candidates seeking flexible work arrangements in data analysis.

What are Weekend Data Analysts?

Weekend Data Analysts are professionals who specialize in collecting, processing, and analyzing data during weekends. They often work in industries that require continuous data monitoring or reporting, such as retail, finance, or customer service. Their responsibilities include preparing reports, identifying trends, and supporting decision-making processes outside of regular business hours. This role is ideal for organizations that need real-time data analysis or have operations extending through weekends.

What Does a Weekend Data Analyst Do?

As a weekend data analyst, you work part-time and use analysis techniques to research trends and discover useful information from data. This job emphasizes getting results and creating reports from data, although the specific responsibilities of this position vary depending on the employer's needs. One of the most common duties of this job is working over the weekend to process data gained throughout the week to prepare a report summarizing the activity for that period. Companies that operate seven days a week often employ weekend data analysts to continue any data analysis tasks from earlier in the week, allowing the organization to function with no interruptions in its data analysis activities.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst; many professionals transition into the field later in life. Success depends on acquiring relevant skills such as data analysis, SQL, and visualization tools, along with continuous learning and certification if needed.

What are the key skills and qualifications needed to thrive as a Weekend Data Analyst, and why are they important?

To thrive as a Weekend Data Analyst, you need a strong background in statistical analysis, data interpretation, and a relevant degree in fields such as mathematics, statistics, or computer science. Familiarity with analytical tools like Excel, SQL, Python, or data visualization platforms such as Tableau is typically required. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for clearly presenting insights and collaborating remotely. These skills ensure timely, accurate analysis and enable data-driven decisions during weekend operations.

Do data analysts work on weekends?

Data analysts typically work during regular business hours on weekdays, but some roles may require weekend work to meet project deadlines or support 24/7 operations. Flexibility depends on the employer, industry, and specific job responsibilities, especially in roles involving real-time data monitoring or client support.

How to get a data analyst job quickly?

To secure a weekend data analyst position quickly, focus on building relevant skills such as proficiency in Excel, SQL, and data visualization tools like Tableau. Obtain certifications if possible, tailor your resume to highlight analytical experience, and apply to roles with flexible schedules or part-time options to increase your chances of rapid employment.

Is there still a demand for data analysts?

Data analysts remain in high demand across various industries due to the increasing reliance on data-driven decision making. Skills in data visualization, SQL, and statistical analysis are highly valued, and job growth is expected to continue as organizations prioritize data insights for strategic planning.

What does a typical weekend shift look like for a Weekend Data Analyst, and how do responsibilities differ from weekday analysts?

As a Weekend Data Analyst, you’ll often work independently or with a smaller team, focusing on real-time data monitoring, reporting, and rapid issue escalation. Weekend shifts can involve handling time-sensitive data tasks, supporting ongoing operations, and preparing summary reports for weekday teams. While core analytical skills remain the same, you may need to troubleshoot urgent data anomalies and ensure smooth handovers to weekday analysts. This role is ideal for individuals comfortable with autonomy and proactive communication.
What are the most commonly searched types of Data Analyst jobs in Portland, ME? The most popular types of Data Analyst jobs in Portland, ME are:
Infographic showing various Weekend Data Analyst job openings in Portland, ME as of July 2026, with employment types broken down into 57% Full Time, 29% Part Time, and 14% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $84,550 per year, or $40.6 per hour.
Financial Data Analyst

Financial Data Analyst

New England Life Care

Scarborough, ME • On-site

$90K - $104K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 24 days ago


New England Life Care rating

6.3

Company rating: 6.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz


Job description

NELC is one of the fastest growing home infusion therapy services companies in New England and is the region’s only non-profit home infusion provider. NELC is a hospital collaborative serving more than 70 hospital systems in Maine, New Hampshire, and Massachusetts. NELC was created by local hospitals to ensure their patients have access to a provider that reflects their commitment to excellence in patient care, quality, and service. Like our owner hospitals, NELC provides patient focused care.

New England Life Care has and continues to build a diverse, inclusive, and authentic workplace, so if you’re energized by this opportunity, we encourage you to apply!

New England Life Care currently has an opening for a Financial Data Analyst. This position typically works Monday through Friday from 8:00am until 5:00pm. Although classified as a remote position, occasional travel is required to a branch location. The ideal candidate for this role will have working knowledge of AI analytics and BI dashboard; audit AI-driven systems and ensure regulatory compliance; and be able to speak to how they have used AI to strengthen forecasts, variance analysis, and reporting in previous roles.


**Although this is a remote position, we are only hiring in the following states: Massachusetts, New Hampshire, and Maine.**



Summary:

Financial and Data Analysts at New England Life Care transform complex financial and operational data into actionable insights that support strategic decision-making while ensuring the accuracy and integrity of all reporting. Candidates in this role are expected to be active practitioners and champions of AI-assisted analytics — leveraging tools such as Claude, Microsoft Power Query, and Power Automate to drive automation, efficiency, and data quality. Beyond their own work, they play a key role in advancing NELC’s broader AI adoption and participate directly in the organization’s AI governance framework. They collaborate with stakeholders across the organization to understand business needs, design analytical solutions, and lead efforts in data collection, reporting, and visualization.

Benefits:

  • Health insurance
  • Dental insurance
  • Vision insurance
  • Generous employer-matched 403b savings program
  • Company paid: Life insurance, Short- and long-term disability insurance
  • Paid time off
  • And much more!


Primary Responsibilities:

  • Collect, clean, and analyze financial and operational data from multiple internal systems; use AI-assisted tools (including Claude) to accelerate data validation, anomaly detection, and cross-source reconciliation
  • Develop and maintain advanced financial and operational models in Excel — as a designer, not just a user — and leverage Power BI for visualization and Power Query for automated data transformation
  • Build and maintain Power Automate workflows to reduce manual reporting steps, automate data refreshes, and improve operational efficiency across finance functions
  • Actively use Claude and other AI tools to generate analytical narratives, draft variance explanations, and identify trends that inform strategic recommendations
  • Champion AI adoption within the organization by training colleagues, sharing practical use cases, and developing repeatable AI-assisted workflows that teams can adopt
  • Serve as an active participant in NELC’s AI governance framework — contributing to the development of responsible use standards, data policies, and compliance guidelines for AI tools in a healthcare environment
  • Contribute to the annual budgeting and quarterly forecasting processes, ensuring alignment with organizational goals and leveraging AI tools to improve accuracy and speed
  • Analyze monthly financial results and trends to deliver actionable insights and strategic recommendations to senior management
  • Identify trends, variances, and anomalies and communicate findings proactively to stakeholders, using AI-generated summaries and dashboards where applicable
  • Structure and analyze large, complex data sets to uncover patterns, trends, and business opportunities
  • Perform routine data quality checks and reconciliations to ensure consistency across data, reporting, and outcomes
  • Collaborate with internal and external stakeholders to gather requirements, validate data, and ensure accuracy in reporting
  • Create clear and compelling presentations and reports based on analytical findings and recommendations
  • Design, maintain, and enhance dashboards and visualizations that communicate key metrics across the organization
  • Maintain knowledge of applicable regulations and policies, including healthcare finance, reimbursement models, and HIPAA requirements as they relate to data and AI use

Educational and Professional Requirements:

  • Bachelor’s degree in Finance, Accounting, Economics, Business Analytics, Data Analytics, or a related field; Master’s degree a plus
  • 2–4 years of experience in financial analysis, data analytics, or a similar role; healthcare industry experience preferred
  • Demonstrated experience using AI tools (e.g., Claude, Microsoft Copilot, or equivalent) in a professional analytics or finance context
  • Proficiency with Microsoft Power Query and Power Automate for data pipeline and workflow automation
  • Familiarity with healthcare finance, reimbursement models, or regulatory compliance is a plus


Preferred Skills:

  • High level of mathematical and analytic ability
  • High-level problem-solving skills
  • A methodical and logical approach to data and process challenges
  • Advanced proficiency in Microsoft Excel (design and modeling, not just data entry)
  • Proficient with Microsoft Office suite and Power Platform tools (Power BI, Power Query, Power Automate)
  • Practical experience with AI-assisted analytics tools and the ability to prompt, evaluate, and integrate AI outputs responsibly
  • Excellent interpersonal, written, and verbal communication skills


''It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.''


Note on AI Governance Participation

New England Life Care is committed to the responsible adoption of AI across its operations. This role is expected to be an active contributor — not a passive observer — to NELC’s AI governance process. That includes helping to define acceptable use guidelines, evaluating tools for HIPAA compliance, flagging potential data risks, and serving as a trusted resource for colleagues adopting AI in their own workflows. Candidates should bring both enthusiasm for AI’s potential and a clear-eyed understanding of its limitations.



EOE


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