Data Analytics Senior
Quantitative Analytics & Modeling
July 23, 2018
Your work falls into three primary categories:
Data Analysis and Platforming
*Collaborate with internal and external data owners or third-party data providers to identify data needed to support Innovation Lab initiatives.
*Work with IT or support the procurement process to acquire and platform data.
*Ensure source data quality aligns with Innovation Lab needs and complies with corporate policies and standards for data.
*Collaborate with IT to mature both on-premises and cloud platform capabilities supporting the Innovation Lab.
Data Mining and Analytics
*Use machine learning, statistics, trend analysis, and/or other data analysis techniques to collect, explore, visualize and identify the right data to be analyzed from internal and external sources.
*Constructs reports, software systems and algorithms to explain or predict relevant business dynamics in order to solve a variety of business problems.
*Assist business analysts with finding patterns and relationships in data.
*May partner with data scientists to prototype predictive models using data, test the model on results outside of the sample size and verify the model in the real world.
Data and AI Tool Evaluations and Proofs of Concept
*Identify and evaluate non-traditional sources of data and new software capabilities that may be of value to the businses and are aligned with our strategy.
*Research and evaluate vendors providing these products and sources.
*Execute IT and procurement processes required to evaluate new technologies and vendors.
*Partner with IT and business partners to plan and execute data and AI proofs-of-concept.
*Document Innovation Lab findings related to data and AI and present recommendations regarding acquiring and leveraging new data, software and approaches for the business.
*Proven ability to deliver information products that are wanted and valued by clients/customers to help solve real-world business problems and challenges
*Experience in relational database structures, research methods, data quality analysis, statistical sampling techniques and reporting
*Proficient in working with large-scale business data sets
*Fluent in scripting and rapid prototyping skills
*Expertise in technologies such as SAS, R, Python, as well as SQL, Java, and/or BI tools such as Hyperion, MicroStrategy and Tableau
*Strong presentation development skills
Key to success in this role
*The ability to solve complex problems in an environment with high uncertainty
*Strong interpersonal and relationship skills
*The ability to partner across organizations to deliver
*The ability to quickly pivot to more promising approaches/alternatives, as appropriate
Top 3 Personal Competencies to possess
*Drive for Execution- Focus on reults rather than the appearance of results
*Customer Focus – Personally engage with customers to learn their needs and seek and use data and feedback to enhance customer outcomes
*Partnership – Build trust and strong partnerships through my own and my team’s actions
*Experience with supervised and unsupervised machine learning algorithms and predictive models
*Natural language processing, natural language generation, conversational AI algorithms, computer vision approaches and tools
*Hadoop, HDFS, Spark
*AWS, Google, Azure cloud environments
*Lean startup, human-centered design-thinking and agile experience
*Project management experience