Collaborating with business leads and value stream owners from Marketing, CX, Sales and Distribution, Operations, Products and Actuarial Teams to identify Data and Analytics (D&A) opportunities, whether descriptive, exploratory, explanatory, or advanced
Harnessing data to answer business questions. This includes data cleaning, transformation, visualization, and application of appropriate statistical and/or AI techniques.
Providing D&A requirements essential to the delivery of D&A initiatives:
Providing Data requirements to the IT and Data Platform Teams, so that data needed for analytics is captured and stored correctly in the right granularity and frequency
Providing Analytics requirements to the Business Intelligence and Reporting Teams (or the Data Acceleration Program), especially on how analytics performance and success measures are defined, computed, and monitored
Providing Analytics requirements to the Advanced Analytics and Gen AI Teams, so that model results align to the planned business action and experience designs
Implementing the end-to-end process of model development (from requirements gathering to deployment and documentation)
Collaborating with business leads in submitting requirements for enterprise and information security risk compliance.
Translating the results of D&A solutions into actionable recommendations and business processes
Proposing how to embed D&A recommendations into business processes and campaign designs
Quantifying the potential impact and realized benefits of analytics solutions within the value stream
Conducting peer reviews (QA, UAT, etc.) and participating in best practice sharing
The role reports to Data Analytics Manager.
Preferred skills
Strong knowledge and understanding of statistical and advanced analytics concepts and methodologies
Familiar with the phases of model development lifecycle including model design, feature engineering and transformation, model selection, and performance monitoring
Experienced with data and analytics tools, such as Python and AWS Sage Maker
Strong knowledge on the governance of models and advanced analytics processes
Good understanding of the ethical principles in analytics and model development
Familiar with model validation processes and documentation, which may include bias and privacy impact assessments
Strong domain knowledge in providing actionable recommendations and insights to different business units, such as Marketing, Customer Experience, Sales, Products, and Operations
Good understanding of marketing attribution, topic modelling, and propensity models
Qualifications
Candidate must possess at least a Bachelor's/College Degree in Computer Science, Statistics, Industrial Engineering or any STEM field.
Minimum 2 years experience in the field of Data and Analytics
Experience in delivering analytical solutions and performing model maintenance
Experience in querying and pulling data from SQL, SAS, and/or AWS Data Stores
Experience working with projects involving large amount of data to conduct exploratory, descriptive, and predictive analytics
Experience in documenting business metrics and requirements, data lineages and flows, user guides
Ability to communicate effectively and work with stakeholders and end-users at all levels.
Can work independently or as part of team
Must be willing to work with and learn new technologies
Must be action- oriented with excellent follow through
Responsibilities
Acting as the D&A Product Owner in a Value Stream
Collaborating with business leads and value stream owners from Marketing, CX, Sales and Distribution, Operations, Products and Actuarial Teams to identify Data and Analytics (D&A) opportunities, whether descriptive, exploratory, explanatory, or advanced
Providing D&A requirements essential to the delivery of D&A initiatives
Translating the results of D&A solutions into actionable recommendations and business processes
Proposing how to embed D&A recommendations into business processes and campaign designs
Quantifying the potential impact and realized benefits of analytics solutions within the value stream
Harnessing data to answer business questions. This includes data cleaning, transformation, visualization, and application of appropriate statistical and/or AI techniques.
Implementing the end-to-end process of model development (from requirements gathering to deployment and documentation)
Translating the results of D&A solutions into actionable recommendations and business processes
Proposing how to embed D&A recommendations into business processes and campaign designs
Governance of analytical models and solutions, which involves the timely testing, validation, and assessment of deployed models.
Conducting peer reviews (QA, UAT, etc.) and participating in best practice sharing
Collaborating with business leads in submitting requirements for enterprise and information security risk compliance.
