Job Description

As a Senior Analyst within Saatchi’s Data Solutions team, you collaborate with cross-functional teams to translate business objectives into actionable analytics initiatives. The goal of this role is to successfully leverage data and advanced analytics resources to support business initiatives. Success for this position is measured by the ability to perform analysis on diverse data sets, and synthesize insights into clear, incisive insights and recommendations that drive business results.

Roles and Responsibilities include:

• Improve on analytic and strategic frameworks by leveraging a deep understanding of industry, company, and consumer content engagement drivers.
• Extract the full value from large complex datasets.
• Work with data science, consumer insights, media and web analytics, and BI teams to leverage data resources and champion new analytics solutions.
• Conduct exploratory and proof-of-concept analyses to identify viable projects that can drive business value.
• Own analysis projects from beginning to end; from conceptualization to presentation and socialization.
• Analyzing and presenting (written and verbal) key learning, insights and optimization recommendations to internal and external clients.

An ideal candidate will have 2-4+ years of experience in a quantitative discipline with a background in mathematics, economics, or statistics.

Qualifications

Candidate experience should include:

• 3+ years of professional experience in a quantitative role, with extensive experience analyzing large sets of data to identify trends, patterns, and correlations that lead to actionable insights and recommendations.
• Ability to clean, process, and transform data as needed to facilitate analysis.
• Project management – strong attention to detail and the ability to prioritize tasks, multitask, and manage time effectively.
• Critical thinking skills – ability to identify gaps, visualize an objective, and leverage data to devise a solution.
• Collaborative mindset needed to bridge the gap between technical and non-technical teams.
• Excellent presentation development and visual storytelling skills.
• Fundamental understanding of data science concepts, methodologies, and techniques. This includes knowledge of statistical analysis, machine learning algorithms, data preprocessing, feature engineering, and model evaluation.
• Familiarity with data tools and languages (Python, R, SQL, Excel).