Data Scientist

Job Description

Exciting opportunity to work with a Big4 Tech company as a Data Scientist, based in London!

12 months contract

Key Qualifications:
• Postgraduate degree (MS or PhD) in a quantitative field of study including economics, statistics, applied mathematics, data science, business, or a related discipline.
• 5-7 years professional experience developing advanced Tableau data visualizations, dashboards and reporting.
• Programming skills in SQL and Python required to develop and maintain custom ETL processes.
• Skills in exploratory data analysis and familiarity with advanced quantitative analysis.
• Experience reporting on web analytics in Adobe, or other web analytics tools.
• Comfortable using modern data technologies. Familiarity with database modelling and data warehousing principles (Snowflake preferred).
• Knowledge of the digital advertising industry, the mobile app economy or related field.
• Familiarity with automated data ingestion processes including APIs.
• Ability to partner effectively with data science and engineering stakeholders to meet the data needs of the business, translating business needs into analytical requirements.
• Ability to communicate the results of analyses in a clear and effective manner.
• Excellent written, verbal, presentation and communication skills.
• Self-motivated and proactive with proven creative, problem-solving, and critical thinking capabilities.

Description:
• Support the Marketing and Sales teams with customer insights and analytics that inform and fulfill strategic objectives and goals.
• Provide Web analytics support to Marketing stakeholders (e.g. producing ad-hoc custom dashboards and Keynote analyses supporting stakeholders).
• Ensure operational excellence by maintaining and improving existing insights development and web reporting processes.
• Quantify the impact of marketing initiatives on customer success and future behavior.
• Drive business analytics projects through all phases, including data quality, data analysis, data visualization, and presentation of results and deliverables.
• Monitor usage metrics, understanding business-based explanations for large scale trends and patterns in customer lifecycle behavior.
• Develop data models and analytical tools for ongoing audience segmentation, benchmarking, trending and competitive analysis.
• Build dashboards, reports and presentations.
• Collaborate with cross-functional team, including Marketing, Sales, Data Insights and Engineering.
Design, conduct and analyze A/B tests to optimize performance of marketing campaigns.