Job Description

The Analytics Solutions Manager Pricing Optimization Data will be an integral part of a global team that delivers on all data-related needs in support of Finances Price Optimization Modeling book of work. The Finance department has shown that machine learning techniques can help set the most ideal product price points to maximize revenue while minimizing customer churn. It now seeks to roll out these advanced analytics capabilities across all products offered by Consumer and Community Banking. This effort will require massive amounts of data to be identified, harvested, curated, and provided to the data science teams to construct new machine learning models.

Key responsibilities for this VP-level position include:

* Collaborate with model developers to understand their book of work, identify data requirements, ensure source data availability in the appropriate data environment and engineer model ready datasets
* Unify and organize pricing data in a fashion that allows successful usage through multiple phases of model development
* Design curated data sets required for cross product and customer centric price optimization managing across D&A, Risk, Finance environments
* Partner with other teams to bring marketing, customer journey, and risk data together with finance data to be used in Pricing models and dashboards.
* Assist with the cloud data migration for the Pricing product while driving alignment to the Firm-wide solution.
* Represent modeling use cases in the Data USe Council forums to ensure appropriate use of firm data

Other responsibilities of the team will include:

* Participate in ongoing product backlog refinement planning with technology partners to drive progress of modeling data needs spanning the full modeling lifecycle
* Manage data across multiple platforms and deployment paths, differentiate between legacy and target state platforms, manage and track tech debt
* Develop data subject matter expertise across a broad range of cross domain data
* Adhere to data use and controls requirements, complete and submit necessary requests for data intake
* Communicate project status, issues, or escalations with key partners or stakeholders
* Support legacy processes and platforms while driving toward target state
* Enable the management of data as a corporate asset: define data (metadata), identify systems of record and authoritative sources, create data quality rules, define security requirements, create data flow diagrams, and administer firm-wide principles, standards, and controls
* Create conceptual and logical models to describe a particular domain of data and use these models to inform the physical design of data-related projects
* Identify areas for efficiency across data domains, such as the elimination of duplicate data or platforms
* Profile, wrangle, and prepare data from diverse sources to support modeling efforts in languages such as Python, SAS, Spark, or Scala
* Conduct business process analysis and identify data needed to support the processes and determine whether the firms data is fit for use within a given process
* Conduct research and development with emerging technologies, determine their applicability to business use cases, document and communicate their recommended use in the firm

Qualifications

* Hands on technical expert that swings across product and data domains to fit most pressing need across data governance, analytics, data staging for modelers, model implementation, new data pipelines and documentation.
* Must exhibit a thorough understanding of data structures, data manipulation, metadata, data security, and data quality management.
* Solid understanding of functions, systems, data environments, and processes that are necessary for the production and utilization of modeling data
* BS or MS in STEM field with quantitative background or equivalent experience/knowledge
* 7+ years of experience as a lead or key participant on data infrastructure related efforts
* Understanding of Hadoop-related technologies & their applications
* Strong command of the SQL language & relational database knowledge
* Knowledge of other languages such as Java/Scala, Python, R, including database design and query optimization
* Strong knowledge of data structures, algorithms and big data tools (Spark, Hive, HDFS, etc.)
* Strong design, coding, debugging and analytical skills, especially across the big data ecosystem
* Advanced analytical thinking and problem-solving skills
* Deep technical knowledge of data infrastructure practices and tools
* Knowledge of version control tools and processes (e.g. Subversion, Git)
* Technical understanding of common RDBMS systems; (e.g. Teradata, Oracle)
* Hands-on experience with various data modeling techniques and tools
* Must have ability to deliver high-quality results under tight deadlines and be comfortable manipulating and summarizing large quantities of data
* Solid communication skills, customer focus and necessary expertise in formal and informal testing techniques as well as quality measurement