The Marketing Data Analyst, Senior supports the overall marketing campaign improvement across media channels (Print, Paid & Earned Digital, Direct Mail, DRTV, Radio), Customer Segmentation, Lead Scoring, Cross Channel Modeling, Cost/Benefit analysis, Pricing Trials, Optimizations, Geo-Spatial analysis, Regression analysis, Competitive Analysis, Forecasting. This position is responsible for data collection, metrics performance management and reporting activities. Responsibilities
(Specific tasks, duties, essential functions of the job)
Knowledge, Skills, and Abilities
- Auditing various data sources such as, but not limited to, Salesforce and Google Analytics to ensure best in class data hygiene, storage, tagging, and retrieval for accurate reporting, analysis, and tool performance
- Extending Inogens 1 st party data with third party data and maintaining robust marketing database
- Support sales and marketing by developing and automating reports and reporting processes integrating data from multiple sources to provide insights that detail proper KPIs against various marketing and sales efforts
- Creating anomaly detections and audit trails to support overall reporting and analysis ensuring data and reporting integrity and accuracy
- Develop models for predicting, optimizing, and forecasting sales and marketing efforts
- Various Ad-Hoc analysis to drive marketing and sales strategies
- Segmenting customer database to create various nurture marketing programs, setting up A/B testing parameters with control vs. treatment cells, measuring test results against hold out samples.
- Clearly distill and articulate complex data analysis, testing outcomes, statistical support to a broader executive team
- Conduct surveys to current database and third-party panels to create feedback loop with current patients and population at large to improve customer service and marketing strategies
- Report on marketing KPIs like leads, conversion rates, website traffic and social media engagement.
- Monitor budget distribution and performance of paid ad campaigns.
- Ensure ROI of online and offline advertising campaigns.
- Maintain regular and punctual attendance.
- Comply with all company policies and procedures.
- Assist with any other duties as assigned.
- Quantitative background and demonstrable ability to analyze and predict trends using descriptive and inferential statistics.
- Must have strong work ethic.
- Excellent oral and written communication skills required.
- Attention to detail is required.
- Effective conflict resolution.
- Analytical & problem-solving skills & ability to multi task.
- Solutions-oriented problem solver.
- Excellent planning, communications, and organizational skills.
- Ability to effectively interface with different departments within the company.
- Applied statistics skills and algorithm familiarity, such as distributions, statistical testing, regression, classification, Bayes, clustering, decision trees, boost, etc.
- Good scripting and programming skills preferred, but not required.
- Data-oriented personality
- Intellectual curiosity of how best to use data and tools that provide insights improving business outcomes.
(Experience and Education)
- Bachelors degree in Marketing, Business, Economics, Finance, Accounting, Mathematics, or related field of study, required.
- 5 years experience in Data Analytics/Data Science role, required; including
- 2 years experience with machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Boost, Regression, NLP Text Mining, Time Series, PCA, etc., required.
- 1 year experience with common data science toolkits, such as Python, R, Weka, Knime, Alteryx, required.
- Advanced knowledge/proficiency in Microsoft Office, required.
- Intermediate knowledge/proficiency in Google Adwords, Google SA360, and Microsoft Ads paid search platforms, required.
- Intermediate knowledge/proficiency in data visualization tools (Tableau, Qlik, Sisense, Tibco, Looker, required.
- Intermediate knowledge/proficiency in databases, such as MongoDB, Cassandra, HBase, Snowflake, required.
- Intermediate knowledge/proficiency in using query languages such as SQL, Hive, Pig, required.
- Google Analytics certified, required.
- A combination of training, education and experience that is equivalent to the qualifications listed above and that provides the required knowledge, skills, and abilities.