Director Data Science
1 month ago
Empower India Data Science team is looking for a senior leader for its Advanced Analytics team in India Marketing organization. This role requires strong experience in Advanced Analytics – Predictive and Prescriptive and capability to produce in-depth analysis that suggests strategic and operational changes. With the focus on Personal Wealth and making Empower a household brand, this role will lead a new team that will focus on analytics informing Lifecycle Marketing and Brand spend optimization.
Role Responsibilities:Identify advanced analytics needs informing Lifecycle Marketing roadmap, working closely with the Lifecycle Marketing teamLead a team of Data Scientists who work on developing models and algorithms that inform optimizations for lead generation (next best action as an example) or brand spends (media mix modeling).Partner closely with Data engineers and architects to ensure required data structures and data models that will enable use cases to be developed and tested around the areas outlined abovePrepare analytics project plans and validate data structures and sources required to support those projectsOwn the Design- Develop- Test- Operationalize cycle for Predictive and Prescriptive analytics, working closely with Data Scientists, Life cycle marketers and Data Engineers.Implement analytical models in production by collaborating with developers and machine-learning engineersConsult and advice on data structures, models and transformations needed to get data ready and ‘ingestible’ for advanced techniquesCollaborate with cross-functional teams to define project requirements, timelines, and deliverables.Apply advanced algorithms on data and develop mechanisms for improving those algorithmsDevise and utilize algorithms and models to mine big-data stores; perform data and error analysis to improve models; clean and validate data for uniformity and accuracyProduce meaningful insights using analytical/data modelling techniques and interpret and justify the results with the business contextEducational Qualification:master's or doctoral degree in computer science, mathematics, statistics, engineering, or a related fieldRequired Experience:12-18 years of experience working in analytics, data science or related experienceProficiency with data mining, mathematics, and statistical analysisAdvanced experience in pattern recognition and predictive modelingextensive experience in developing and deploying ML solutions using various tools, frameworks, and languagesExperience with Excel, PowerPoint, Tableau, SQL, and programming languages (ex: Java/Python, SAS)Ability to work effectively in a dynamic, research-oriented group that has several concurrent projectsAttention to detail, and should be open to learn quickly on new technologies and statistical techniques in analyticsRequired skills and competencies:Technical expertise regarding data modelling using statistical techniques, data mining, generate and automate BI reportsStrong knowledge of and experience with the data modelling techniques like Time Series, Regression, Segmentation, Clustering, Market Mix, Machine Learning, AI.Strong analytical skills to be able to understand the complex business problem, collect and analyze the data and able to interpret the resultsLead and drive cross functional projectsStrong written and verbal communication skill and be able to present the results to the senior stakeholdersKnowledge of US financial services sector is preferredSelf-motivation, excellent accountability and ownership skillsWe are an equal opportunity employer with a commitment to diversity. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to age, race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.
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