Company:
Prosperix
Location: San Francisco
Closing Date: 21/10/2024
Salary: £150 - £200 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description
Minimum Requirements
- Bachelor's degree in a technical, quantitative, or business field
- 4+ years of experience in Data science, statistics, and quantitative data analysis
- Proficiency in SQL or another programming/scripting language (Python/R)
- Strong communication skills and attention to detail
- Knowledge of software product development processes and experimentation (e.g., AB testing)
- Advanced SQL skills are required
- Experience in independently managing complex projects
- Ability to present results and recommendations to executive audiences
- Willingness to learn new analytical techniques and frameworks
- Excellent analytical, quantitative, and interpersonal skills
- Leadership and self-direction abilities
Responsibilities
- As a member of the Ads Product finance team, we are responsible for growing the Client's Ads business through holistic financial support and analytical insight.
- The project will be centered around supporting the Client's Search Ads team.
- Acting as a business data scientist on the finance team, we ensure that the Client makes sound financial decisions.
- Your work, whether it's modeling business scenarios or tracking performance metrics, is used by our leaders to make strategic company decisions.
- The Business Data Analyst serves as a key member of the finance team, ensuring sound financial decisions through modeling business scenarios, tracking performance metrics, and providing analytical insight for strategic decision-making.
- Collaborate with project stakeholders to uncover user/advertiser insights, identify trends, and suggest growth opportunities.
- Work with a team of analysts to collect and analyze large-scale datasets, automating processes and creating insightful visualizations.
- Conduct in-depth analysis of business success metrics and facilitate cross-functional collaboration to establish key success metrics for decision-making.
- Develop robust analyses and models to drive cost efficiencies and monitor value metrics.
- Produce regular revenue reports with key insights for the leadership team.
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