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Data Science Jobs in Portland, ME (NOW HIRING)

Bachelor's degree in Data Science, Computer Science, or a related field * Minimum of 3-5 years of experience in data management, analytics, or similar, preferably within a marketing environment

Bachelor's degree in Data Science, Computer Science, or a related field * Minimum of 3-5 years of experience in data management, analytics, or similar, preferably within a marketing environment

DevOps Engineer

Portland, ME · On-site

$54.75 - $75/hr

... data scientists to improve platform capabilities and operational efficiency • Maintain platform documentation and communicate project status, risks, and progress to stakeholders You will be a good ...

Bachelor's degree in life sciences, health, clinical, biological, or mathematical field. * No less than 7 years of direct clinical data management experience * 5+ years in a Lead Clinical Data ...

Bachelor's degree in life sciences, health, clinical, biological, or mathematical field. * No less than 7 years of direct clinical data management experience * 5+ years in a Lead Clinical Data ...

Lead cross-functional collaboration across engineering, data science, integrations, legal, content, commercial, and country organizations to turn strategy into shipped outcomes * Own end-to-end ...

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Showing results 1-20

Data Science information

See Portland, ME salary details

$38.4K

$125.6K

$201K

How much do data science jobs pay per year?

As of Jul 19, 2026, the average yearly pay for data science in Portland, ME is $125,576.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,800.00 and $139,100.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
What are the most commonly searched types of Data Science jobs in Portland, ME? The most popular types of Data Science jobs in Portland, ME are:
What are popular job titles related to Data Science jobs in Portland, ME? For Data Science jobs in Portland, ME, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Portland, ME look for? The top searched job categories for Data Science jobs in Portland, ME are:
What cities near Portland, ME are hiring for Data Science jobs? Cities near Portland, ME with the most Data Science job openings:
Infographic showing various Data Science job openings in Portland, ME as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 16% Part Time, and 4% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $125,576 per year, or $60.4 per hour.
Marketing Operations Analyst

Marketing Operations Analyst

FocusKPI

Biddeford, ME • On-site

Full-time

Posted 28 days ago


Job description

FocusKPI is looking for a Marketing Operations Analyst to join one of our clients, a high-tech SaaS company.

As a Marketing Operations Analyst on the Marketing Operations & Technology team, you’ll help share the client's marketing data strategy. This includes driving data governance and consistency across systems, enabling effective audience targeting for strategic marketing initiatives, and ensuring compliance with privacy regulations such as GDPR and CCPA. This is a hands-on technical role, ideal for someone who thrives in ambiguity, works autonomously with large data sets, and brings structure to complex problems. The role involves writing complex SQL to access data in our warehouse, while also building and activating audiences through our customer data platform (CDP). The ideal candidate is innately curious and passionate about identifying novel approaches to derive value from disparate data sets and highly motivated to improve your skillset around the modern data stack.

Responsibilities:

  • Audience Targeting: Develop and implement audience segmentation strategies using advanced SQL queries and data manipulation to support targeted campaigns.
  • Data Governance and Management: Gain a comprehensive understanding of our data quality and flow processes, while identifying and developing solutions to enhance data usability and accessibility.
  • Compliance Oversight: Ensure all marketing data practices adhere to privacy regulations, including GDPR and CCPA.
  • Data Integration: Collaborate with cross-functional teams such as IT and engineering to integrate data from various sources into the customer data platform (CDP) for comprehensive analysis.
  • Analytics and Reporting: Design and execute data analyses to derive actionable insights, providing stakeholders with regular reports on marketing performance and audience behaviour.
  • Collaboration and Communication: Collaborate cross-functionally with marketing stakeholders to gather evolving requirements, design effective solutions, and clearly communicate nuances of the deliverable to ensure alignment and actionable outcomes.

Requirements:

  • Bachelor’s degree in Data Science, Computer Science, or a related field
  • Minimum of 3-5 years of experience in data management, analytics, or similar, preferably within a marketing environment
  • Proficiency in SQL for data manipulation and analysis. Comfortable with Python.
  • Experience working within data platforms like Databricks/Snowflake, and analytics modeling platforms such as Tableau
  • Strong analytical and problem-solving skills with the ability to interpret complex data sets and generate actionable insights.
  • Exceptional attention to detail and a commitment to maintaining high data quality standards.
  • Demonstrates innate curiosity, comfort with ambiguity, and a proactive approach to identifying opportunities for improvement and innovation in data processes

No C2C resumes are considered


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About FocusKPI

Sourced by ZipRecruiter

Industry

Computing infrastructure providers, data processing, web hosting

Company size

51 - 200 Employees

Headquarters location

Santa Clara, CA, US

Year founded

2010