Senior Data Analyst

About the client:

We empower potential by creating educational solutions that inspire boundless possibilities for every student, every day. We are passionate about innovating together to support educators in creating those special moments when students experience the joy of learning at its best.
We also empower our team through a strong culture focused on career growth and development, flexible work from home arrangements, interesting and meaningful work, and a supportive and connected team. As a remote-friendly company, hybrid and remote team members work from states across the U.S. and internationally. The majority of our US employees enjoy the opportunity to work from home, or in a hybrid capacity in our offices in Tempe, AZ (headquarters), Austin, TX, Petaluma, CA, Rock Rapids, IA, Grand Rapids, MI, or Bloomington, MN.

Requirements:

• Education: Bachelor’s degree in Data Science, Mathematics, Statistics, Computer Science, or a related field and at least two years of experience or equivalent combination;
• Experience: 3-5+ years in a data science role with a focus on developing and deploying practical machine learning solutions.

Technical Skills:

• Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, etc.), R, and SQL;
• Experience with big data tools and platforms such as Spark, Hive, Snowflake, and AWS Redshift;
• Strong statistical modeling skills (regression, classification, time series forecasting, etc.);
• Familiarity with data visualization tools like Tableau or Power BI.

Soft Skills:

• Excellent communication skills to present findings to technical and non-technical audiences;
• Strong collaboration and stakeholder management capabilities;
• Self-starter with a pragmatic approach to problem-solving, capable of working with minimal oversight.

Responsibilities:

• Analyze structured and unstructured data to build, deploy, and improve machine learning models and statistical analyses that address business needs;
• Collaborate with cross-functional teams (content, product, assessment, engineering) to identify opportunities, explore data sets, and deliver scalable, actionable insights;
• Design and execute experiments (e.g., A/B testing) to optimize product features and improve user engagement, growth, and retention;
• Develop subject matter expertise across various domains to support a diverse range of projects;
• Translate complex analytical findings into clear, concise recommendations for technical and non-technical stakeholders, including senior leaders;
• Work with data engineering teams to implement and operationalize models, data pipelines, and other scalable solutions;
• Create compelling visualizations to effectively communicate data insights and trends;
• Stay updated on emerging data science tools and techniques to continuously enhance methodologies;
• Other duties as required.