Google Marketing Platform Data Analyst

Technical Skills 1. Google Marketing Platform Certification • Google Cloud Certified Professional Machine Learning Engineer Proficient in the areas of model architecture, data and ML pipeline creation, generative AI, and metrics interpretation • Certified in Google Analytics Proficiency in analyzing campaign performance using GMP tools and Google Analytics, with a focus on metrics like CPC, CPM, ROI, and conversion rates • Certified in Google Display & Video 360 Experience in programmatic advertising, creating and managing display and video campaigns across multiple platforms • Certified in Google Campaign Manager 360 Analyzing campaign performance, measuring ROI, and generating insights. • Data Analytics Proficiency in analyzing campaign performance using GMP tools and Google Analytics, with a focus on metrics like CPC, CPM, ROI, and conversion rates • Automation & Integration Ability to leverage automation tools and integrate GMP products for streamlined campaign management and reporting 2. Data Analysis and Visualization: • Proficiency in data analysis tools like SQL, Python (with libraries like Pandas, NumPy, and Matplotlib), or R. • Experience with data visualization tools like Tableau, Looker, or Google Data Studio to create compelling reports and dashboards. 3. Digital Marketing Fundamentals: • Knowledge of digital marketing concepts such as SEO, SEM, social media marketing, and email marketing. • Understanding of how these channels interact and contribute to overall marketing goals. 4. Digital marketing prediction with Shapley & Markov models • Familiarity with digital marketing concepts, customer journeys, and multi-channel attribution (e.g., paid search, social media, email). Understanding of attribution models, including first-click, last-click, and multi-touch • Strong understanding of Shapley values from cooperative game theory, used to fairly attribute conversions to marketing channels based on their contributions. Familiarity with Python/R libraries like shap for computing Shapley values and interpreting feature importance, with the ability to explain channel contributions to overall marketing success • Understanding of Markov models, focusing on state transitions between marketing touchpoints and their probabilities. Knowledge of using Markov models to analyze conversion probabilities and attribute value to channels. Proficiency in Python/R libraries like markovify for predicting customer transitions across channels 5. Prediction of Propensity to buy using Bayesian Models • Solid understanding of Bayesian probability, including prior, likelihood, and posterior distributions. Knowledge of Bayesian inference to update probabilities based on new data using Bayes' Theorem • Understanding customer behavior and business context (e.g., e-commerce, retail, etc.) to design relevant Bayesian models tailored to propensity-to-buy prediction 6. Prediction of Budget using Q-Learning Models • Understanding key RL principles like rewards, states, actions, and policies. Familiarity with exploration vs. exploitation trade-offs • Familiarity with optimization strategies for improving model performance and hyperparameter tuning Analytical Skills 1. Data-Driven Decision Making: • Ability to analyze complex data sets and extract meaningful insights to inform marketing strategies. • Skill in translating data into actionable recommendations. 2. Problem-Solving: • Ability to identify and troubleshoot data quality issues. • Capacity to develop innovative solutions to marketing challenges. 3. Communication: • Effective communication skills, both written and verbal, to present findings to stakeholders. • Ability to collaborate with cross-functional teams. Experience • Minimum 4-5 years of experience in a data analyst or digital marketing role. • Experience working with Google Marketing Platform tools is a significant advantage. • Experience in a specific industry (e.g., e-commerce, finance, media publication) can be a plus. • Fresh graduate with strong Google Marketing Platform knowledge is welcome to apply. Additional Skills • Experience with other digital marketing tools (e.g., Adobe Analytics, Salesforce Marketing Cloud) can be beneficial. • Certification in Google Marketing Platform tools or related fields can be a credential.