Transform large datasets into actionable business insights, drive operational excellence, and support strategic decision-making in a fully remote role.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Remote--Senior Data Analyst / Data Scientist
Location: 100% Remote
Travel: Up to 25%
IntePros is seeking a Senior Data Analyst / Data Scientist to join one of our growing clients in a fully remote role. This position is responsible for transforming large, complex datasets into actionable business insights that drive operational excellence and strategic decision-making. The ideal candidate combines advanced analytical skills with strong business acumen and has experience building predictive models, dashboards, and scalable reporting solutions.
Responsibilities
Data Analysis & Business Insights
- Analyze current and historical business data to identify trends, opportunities, and risks that improve operational performance and financial results.
- Develop actionable recommendations that support strategic business initiatives and continuous improvement efforts.
- Perform ad hoc analyses for executive leadership and cross-functional teams.
Data Extraction & Analytics
- Extract, query, and analyze large datasets from multiple enterprise systems using SQL and Python.
- Build statistical models, forecasting models, and predictive analytics solutions to improve business decision-making.
- Apply advanced analytical techniques, including trend analysis, regression, forecasting, and statistical modeling.
Reporting & Visualization
- Design, develop, and maintain interactive dashboards, KPI reporting, and executive-level presentations.
- Create automated reporting solutions that improve efficiency and reduce manual effort.
- Present analytical findings in a clear, concise, and business-focused manner.
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Data Quality & Process Improvement
- Validate data accuracy and identify inconsistencies across multiple data sources.
- Partner with Data Engineering and Business Intelligence teams to resolve data quality issues.
- Develop reusable analytical processes and automation that improve reporting scalability.
Cross-Functional Collaboration
- Work closely with Operations, Finance, Quality, IT, and Business Intelligence teams to understand business challenges and deliver data-driven solutions.
- Translate business requirements into analytical models and reporting solutions that support enterprise objectives.
Required Qualifications
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Business Analytics, Engineering, Economics, or a related field.
- Experience as a Senior Data Analyst, Business Intelligence Analyst, Analytics Consultant, or similar role.
- Hands-on experience applying predictive modeling, statistical analysis, or machine learning techniques.
- Advanced SQL skills, including complex queries, joins, CTEs, window functions, and stored procedures.
- Strong Python programming experience for data analysis, automation, and model development.
- Experience working with large enterprise datasets and multiple structured data sources.
- Experience creating dashboards and KPI reporting using Power BI, Tableau, QlikSense, or similar visualization tools.
- Strong analytical, problem-solving, and communication skills.
- Ability to manage multiple priorities in a fast-paced environment while working independently and collaboratively.
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Preferred Qualifications
- Master's degree in Data Science, Analytics, Statistics, Computer Science, or a related discipline.
- Experience within healthcare, biotechnology, pharmaceutical, manufacturing, or other highly regulated industries.
- Experience with cloud data platforms such as Snowflake, Azure, AWS, or Google Cloud.
- Knowledge of predictive analytics, forecasting, optimization techniques, and statistical experimentation.
- Experience automating recurring reporting and analytical workflows.
- Experience supporting executive leadership with strategic analytics and business insights.
Technical Skills
- SQL: Advanced querying, joins, CTEs, window functions, stored procedures
- Python: Pandas, NumPy, Scikit-learn, Matplotlib
- Business Intelligence: Power BI, Tableau, QlikSense
- Databases: SQL Server, Snowflake, Oracle
- Analytics: Predictive modeling, forecasting, regression analysis, statistical analysis
- Reporting: Dashboard development, KPI reporting, data visualization
- Additional Tools: Excel, PowerPoint, Git, Jupyter Notebook, ETL concepts, data validation, automation, Jira, ServiceNow
This is an excellent opportunity for an experienced analytics professional who enjoys solving complex business problems, influencing strategic decisions through data, and building scalable analytical solutions in a collaborative, data-driven environment.
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