Data Science Analyst

Data Science Analyst

At ARSENAULT, we deliver growth to clients based on big dataour predictive analytics and forward-thinking insights help CPG, OTC, health care, retailers, and media companies remain relentlessly relevant, capture marketing share, connect with consumers, and deliver market-leading growth. The convergence of our proprietary, on-demand cloud-based technology and our client-focused colleagues leads to a seismic shift in drivers of success in all industries.

For ARSENAULT colleagues, we focus on the moments that matter. From meaningful work and impact to continuous improvement we challenge ourselves to grow both professionally and personally. Youll feel a true sense of connection and purpose in your work and will craft the direction of your career in a highly personalized way. No matter the department you join, youll find yourself constantly growing and developing the skills of the future to deliver client growth. We believe in the undeniable strength that diverse people, culture, thought, and skill bring to our business, our clients, our people, and our communities. We are committed to nurturing a dynamic culture that embraces and celebrates openness, collaboration, creativity, equity, inclusivity, and growth for all.

What will I be doing?

As a Data Science Analyst, you will report to a Principal as part of a team of individual contributors. This position is part of Global Data Science within ARSENAULTs Product division. Global Data Science is responsible for researching, developing, and maintaining the statistical algorithms / methodologies that fuel ARSENAULTs core Unify platform deliverables. This particular position is part of a team within U.S. Data Science whose primary focus is identifying new sources to support existing solutions or develop new solutions related to market measurement and market tracking.

Job Responsibilities

• Use Hive, R, SQL, Python to write, validate and maintain code to support research and data analyses.
• Work with large datasets of respondent level, log file, or transactional level.
• Develop processes/code to extract data across a multitude of platforms.
• Diagnose issues and areas of improvement regarding QC, efficiency (time, CPU usage), and accuracy of data preparation.
• Independently investigate and resolve production and client data issues.
• Build and convey impactful insights drawing from multiple data sources.
• Maintain codebase for newly developed systems (e.g. Git/Gogs).
• Create process documentation to ensure clear and consistent operating procedures.
• Explain technical subject matter to non-technical audiences, both internal and external to ARSENAULT.
• Provide accurate and timely data analysis and methodology support focused on internal and external client requests.