Sr. Data Analyst

The Senior Data Analyst plays a critical role in leading advanced data analysis initiatives that uncover meaningful patterns and trends, supporting data-informed decision-making across the organization. This role involves independently sourcing, transforming, and interpreting diverse datasets and translating findings into clear, actionable insights through advanced visualizations and reports tailored for managers and functional leads. By strengthening our data-driven approach, the Senior Data Analyst will play a pivotal role in turning raw information into measurable improvements that support our mission and align with organizational objectives.

Essential Functions And Responsibilities

• Partner with directors and managers across departments to proactively identify opportunities where data analytics can enhance operational effectiveness and support business goals.
• Lead the design, implementation, and deployment of predictive and prescriptive models.
• Continuously evaluate, refine, and optimize models to improve accuracy, reliability, and business relevance.
• Translate machine learning outputs into actionable recommendations that support data-informed decisions by directors and managers.
• Deliver impactful reports, dashboards, and data stories tailored for executive audiences and non-technical stakeholders, clearly linking analytics to strategic recommendations.
• Design and implement robust data collection strategies from multiple sources (enterprise databases, APIs, external data feeds, unstructured data) while ensuring data integrity and accessibility.
• Lead data cleaning, transformation, and validation processes, establishing best practices for data quality, governance, and reliability.
• Drive the development and deployment of predictive and prescriptive models to support strategic planning, resource allocation, and operational optimization.
• Collaborate with data analysts, developers, and technology leaders to define data architecture, integration requirements, and system implementations.
• Provide guidance to junior analysts and contribute to building data literacy across teams.
• Proactively research and recommend emerging data technologies, tools, and practices to strengthen analytical capabilities and maintain competitive advantage.

• Bachelor's degree in Data Science, Computer Science, Information Systems Management, or a related field.
• 3-5 years of relevant professional experience in data analysis, including designing dashboards, delivering reports, and supporting operational or business decisions.
• Strong programming experience in Python (Pandas, NumPy, Scikit-learn) or R, with advanced SQL skills for complex queries and database management.
• Demonstrated knowledge of ETL frameworks and data warehousing principles.
• Strong knowledge of database design, relational and dimensional modeling, and data mining techniques.
• Hands-on experience applying advanced statistical concepts, supervised/unsupervised learning, and machine learning algorithms to solve real-world business problems.
• Proven ability to design, implement, and deploy predictive and prescriptive models.
• Ability to evaluate model performance, optimize accuracy, and translate outputs into actionable business strategies.
• Strong experience with data visualization tools (Power BI, Tableau, or similar).
• Familiarity with cloud-based data platforms (Azure, AWS, Google Cloud) and associated analytics services.
• Experience with web analytics platforms (Google Analytics, Adobe Analytics) is a plus.
• Proficiency in Microsoft Office Suite (Word, Excel, PowerPoint), as well as Outlook, Teams, and SharePoint.
• Excellent written and verbal communication skills, with confidence presenting to directors & managers.
• Ability to translate complex data into clear, actionable insights for diverse audiences.
• Collaborative mindset and willingness to share knowledge with team members.
• Proficient in both written and spoken English.
• Exceptional analytical, problem-solving, and critical-thinking skills.
• Ability to manage multiple priorities and deliver high-quality work independently.

• Limited to typical office environment such as walking, sitting, typing, using office equipment, and occasional lifting of boxes or luggage during travel.
• Occasional national or international travel may be required.
• Working out of the official hours and on weekends may be required.