Senior Data Analyst

MJH Life Sciences is a company that values determination and teamwork, seeking to hire a Senior Data Analyst to enhance their data-driven culture. The role involves leading complex data analysis projects, mentoring junior analysts, and collaborating with various teams to provide actionable insights that drive strategic decision-making.

Responsibilities:

• Lead advanced data analysis projects, transforming raw data into actionable insights
• Develop and maintain dashboards, reports, and KPIs to support strategic initiatives
• Partner with business leaders to identify opportunities for growth, optimization, and innovation
• Mentor and support junior analysts, providing training and guidance on best practices
• Collaborate with engineering and data teams to ensure data accuracy, integrity, and accessibility
• Identify, troubleshoot, and resolve data quality issues
• Conduct statistical and predictive analyses to support business forecasts and performance modeling
• Communicate findings through compelling data stories, presentations, and visualizations tailored to stakeholders
• Contribute to continuous improvement of data processes, governance, and standards

Requirements:

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or related field
• 4–6 years of data analysis or business intelligence experience, preferably in healthcare, life sciences, publishing, or a related industry
• Proven track record of delivering insights that drive business results
• Advanced proficiency in SQL and data querying
• Strong experience with BI and visualization tools such as Power BI, Tableau, or Looker
• Strong knowledge of Excel (advanced functions, pivot tables, data modeling)
• Experience with statistical analysis using Python, R, or SAS
• Excellent written and verbal communication skills with the ability to present findings clearly
• Strong organizational and project management skills
• Experience with big data tools and cloud platforms (Snowflake, AWS, Azure, GCP)
• Knowledge of ETL processes and data warehousing
• Familiarity with machine learning or predictive modeling techniques
• Background in healthcare or life sciences data analysis