Senior Analyst

Roles and responsibilities

Search: Experiment with text ads, bidding, and campaign structures on Google, Bing, Baidu, Naver, and other search engines. Adapt to new product features and roll out changes from successful tests
Display: Test, analyze, and optimize campaigns on Facebook, Twitter, Instagram, and others
Modeling: Analyze the vast amounts of data generated by experiments, develop models we can use for optimization, and build dashboards for account managers
Data Collection & Analysis:

Collect, analyze, and interpret large datasets from various sources (e.g., internal systems, market data, or third-party reports) to provide business insights.
Apply advanced analytics techniques, including regression models, forecasting, and scenario analysis, to generate actionable findings for decision-makers.
Use statistical tools to identify trends, correlations, and patterns in data, then present the results in a clear and impactful manner.
Reporting & Presentation:

Produce high-quality, clear, and concise reports, presentations, and dashboards that summarize analytical findings for executive leadership and stakeholders.
Regularly present complex data findings and strategic insights to senior management and business leaders, ensuring data is translated into actionable recommendations.
Provide regular performance reports on key metrics and key performance indicators (KPIs) related to business operations, financials, or specific projects.
Strategic Insights & Recommendations:

Provide strategic insights and recommendations based on analytical findings, helping to drive business improvements, efficiency, and profitability.
Participate in high-level decision-making by advising on potential outcomes of different business strategies or initiatives, using data and modeling to forecast impacts.

Desired candidate profile

Bachelor’s Degree or higher from top university in a quantitative subject (computer science, mathematics, engineering, statistics or science)
Ability to communicate fluently in English
Exposure to one or more data analysis packages or databases, e.g., SAS, R, SPSS, Python, VBA, SQL, Tableau
Good numerical reasoning skills
Proficiency in Excel
Intellectual curiosity and analytical skills
Advanced proficiency in data analysis tools such as Excel (pivot tables, advanced functions), SQL, and data visualization tools (e.g., Power BI, Tableau, Looker).
Familiarity with analytical programming languages such as Python or R for statistical analysis and modeling is highly valued.
Experience with statistical analysis and predictive modeling techniques (e.g., regression analysis, time series analysis).
Working knowledge of ERP systems (e.g., SAP, Oracle) or CRM platforms (e.g., Salesforce) depending on the organization's needs.
Business & Analytical Acumen:

Deep understanding of business operations, financial principles, or industry-specific dynamics (depending on the focus of the role).
Ability to evaluate large datasets, identify trends, patterns, and provide actionable insights.
Strong critical thinking and problem-solving skills to synthesize data and propose well-grounded solutions.