Data Analyst Data Science Jobs in Portland, OR (NOW HIRING)

Impact Scale is seeking an experienced, highly analytical Data Analystwith a strong background in data analytics, data science, statistics, or a related quantitative field. This role will be responsible for transforming complex datasets into actionable insights that drive business strategy, operational performance, and informed decision-making across the organization.

The ideal candidate has hands-on experience working with large and complex datasets, querying and manipulating data, developing dashboards and reporting systems, identifying meaningful trends, and applying analytical and statistical methods to solve business problems.

In this role, you will partner with cross-functional teams and leadership to define key performance indicators (KPIs), analyze business performance, identify opportunities and risks, improve data quality and reporting processes, and provide data-driven recommendations that influence strategic and operational decisions.

• Analyze large and complex datasets from multiple sources to identify trends, patterns, correlations, anomalies, and business opportunities.

• Translate business questions into structured analytical approaches and measurable outcomes.

• Apply statistical and analytical techniques to evaluate performance, test hypotheses, and identify the underlying drivers of business results.

• Develop data models, forecasts, segmentation analyses, and other quantitative analyses to support business decisions.

• Proactively identify meaningful insights, risks, and opportunities rather than relying solely on predefined reporting requests.

• Present analytical findings and recommendations in a clear, concise, and actionable manner to leadership and internal stakeholders.

• Develop, maintain, and improve dashboards, reports, and performance measurement systems.

• Define, monitor, and analyze key performance indicators (KPIs) across multiple areas of the business.

• Build scalable and reliable reporting processes that improve visibility into business performance.

• Create effective data visualizations that communicate complex findings to both technical and non-technical audiences.

• Validate reporting accuracy and investigate discrepancies, anomalies, or changes in performance.

• Query, clean, transform, and validate data from multiple systems and data sources.

• Identify data quality issues and collaborate with relevant teams to improve data accuracy, consistency, and reliability.

• Develop repeatable analytical processes and documentation to support scalable reporting and analysis.

• Maintain clear definitions and documentation for key metrics, datasets, and analytical methodologies.

• Partner with leadership and cross-functional teams to understand business objectives and translate them into analytical requirements.

• Conduct deep-dive analyses to understand business performance and identify opportunities for growth, efficiency, and optimization.

• Support strategic planning through forecasting, scenario analysis, business modeling, and performance analysis.

• Evaluate the effectiveness of business initiatives and provide recommendations based on measurable results.

• Identify workflow and operational inefficiencies through data and recommend improvements.

• Serve as a trusted analytical partner to teams across the organization.

• Work with stakeholders to define reporting requirements, KPIs, analytical questions, and success metrics.

• Communicate analytical findings and recommendations effectively to both technical and non-technical audiences.

• Support cross-functional projects by establishing measurement frameworks and analyzing results.

• Bachelor's degree in Data Science, Data Analytics, Statistics, Mathematics, Computer Science, Economics, Engineering, or another quantitative field required. Master's degree is a plus.

• 3–5+ years of professional experience in data analytics, data science, business intelligence, or a similar highly analytical role.

• Demonstrated experience analyzing complex datasets and translating findings into actionable business recommendations.

• Strong SQL skillsand experience querying, joining, transforming, and validating data across multiple datasets.

• Advanced proficiency in Microsoft Excel and/or Google Sheets, including complex formulas, data modeling, and analytical workflows.

• Experience building dashboards and data visualizations using tools such as Power BI, Tableau, Looker, Looker Studio, or similar platforms.

• Strong understanding of statistical concepts, analytical methodologies, and data interpretation.

• Experience with Python, R, or another analytical programming language strongly preferred.

• Experience with data cleaning, transformation, validation, and quality assurance.

• Ability to independently structure and solve ambiguous analytical problems.

• Strong critical thinking and problem-solving skills with exceptional attention to detail.

• Ability to communicate complex analytical concepts and findings clearly to non-technical stakeholders.

• Strong organizational skills and the ability to manage multiple priorities in a fast-paced environment.

• Experience applying statistical modeling, predictive analytics, experimentation, or machine learning techniques to business problems.

• Experience working with cloud-based data warehouses or modern data platforms.

• Familiarity with data pipelines, ETL/ELT processes, APIs, or data integration workflows.

• Experience developing forecasting, attribution, segmentation, or performance models.

• Demonstrated ability to independently identify analytical opportunities and develop solutions from initial question through final recommendation.

• Delivers accurate, timely, and actionable analysis that directly informs business and strategic decisions.

• Goes beyond surface-level reporting to identify the underlying drivers of business performance.

• Develops scalable dashboards, analytical models, and reporting systems that leadership can rely on.

• Identifies trends, anomalies, risks, and opportunities before they become obvious through standard reporting.

• Improves the quality, consistency, and accessibility of data used across the organization.

• Effectively translates complex data into clear recommendations for technical and non-technical stakeholders.

• Becomes a trusted analytical resource for leadership and cross-functional teams.

• Contributes to a culture of rigorous, data-driven decision-making across the organization.

• Generous benefits package, including comprehensive health insurance, retirement savings, and paid time off.

• Professional development opportunities and education reimbursement.

• Catered lunches, full coffee bar, and paid parking.