Experienced Data Analyst II – Blithequark Data Ventures and Remote Work Opportunities in Data Entry and Analysis
Introduction to Blithequark
At blithequark, we are passionate about helping people live better lives through our mission to provide excellent products and services. As a leader in the retail industry, we believe in the power of data to drive business decisions and improve customer experiences. Our Data Ventures team is at the forefront of this effort, working to unlock the full value of our data and create innovative solutions that benefit our customers and partners. If you are excited about the potential of data to drive business success and improve people's lives, we invite you to join our team as a Data Analyst II.
Job Overview
Key Responsibilities
- Research, collect, and analyze large datasets to identify trends, patterns, and insights that inform business decisions
- Develop and maintain dashboards and reports to track key performance metrics and provide data-driven insights to stakeholders
- Collaborate with product teams to design and implement data-driven solutions that drive business growth and improve customer experiences
- Work with data engineering teams to design and implement data pipelines and architectures that support business needs
- Develop and maintain data models and databases to support business intelligence and analytics
- Stay up-to-date with industry trends and emerging technologies in data analytics and science
Essential Qualifications
- Bachelor's degree in a quantitative field, such as mathematics, statistics, computer science, or engineering
- At least 2 years of experience in data analysis, data science, or a related field
- Strong analytical and problem-solving skills, with the ability to collect and analyze large datasets
- Experience with data visualization tools, such as Power BI, Tableau, or Looker
- Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams
Preferred Qualifications
- Master's degree in a quantitative field, such as mathematics, statistics, computer science, or engineering
- Experience with machine learning algorithms and statistical modeling
- Experience with data engineering tools, such as SQL, Python, or Java
- Experience with cloud-based data platforms, such as AWS or Google Cloud
- Experience with data governance and data quality tools, such as Collibra or SAS