Data Science Product Owner

Job Req #: 21-12505Job Description: Data Science Product OwnerLocation: Denver, CO. Ideally work two days in office and three from home. Remote in the Denver metro area works, also. Job Type: FTE/Direct HireThe base salary range for this position is $125,000 to $140,000. This range is estimated for this role. Actual pay may be different. s and s are welcome to apply. My client cannot transfer a visa. Our client is a global Asset Management group that offers a range of financial products to individuals, intermediary advisors and institutional investors. Unlike most financial services organizations, they are technology obsessed and are always investing in the newest and latest technologies. They have a work hard/play hard culture where those who are most open to change are the ones who truly excel. Key Responsibilities: My client is evolving its use of analytics in its Distribution organization. They are striving to move more towards predictive / prescriptive analytics to drive sales and marketing activities. Initially, this role will focus on the leadership of data engineering activities needed to drive their descriptive analytics. These activities include the creation of datasets in their cloud data warehouse using Databricks and Snowflake, acting as an Agile Product Owner. In the future, this role will focus more on data science activities, and you will be responsible for the product vision for the Client Analytics Data Science team. You will direct a team, guiding them while building a portfolio of machine learning models used to drive operational analytics. You will use your past experience, domain knowledge, and business relationships to suggest what models should be developed. You will use SQL and visualization tools such as Tableau or Power BI to profile and gain an understanding of the data sources for Analytics to use in our analytic datasets. You will be a part of an agile data team that provides data engineering and machine learning services for my client, which include data such as Assets Under Management (AUM), interactions, competitive intelligence, opportunities, revenue / profitability, and others. These are then used by their business partners to drive insights. You will help to investigate anomalies and issues in the data within the course of regular business as usual (BAU) activities, as well as prioritizing this work for bi-weekly sprints. Act in the capacity of Data Science Product Owner, supporting the Client Analytics product, and doing the following:

• Develop the product vision.
• Drive creation of predictive and prescriptive analytic models for use in distribution sales and marketing activities.
• Author user stories as Agile Product Owner that inform development activities.
• Perform data analysis / troubleshooting on BAU issues that come up during a day / week related to analytic models.
• Build analytic models such as Recommendation Engine, Churn, Segmentation, etc. or lead the creation thereof.
• Assist / lead in data engineering efforts that are needed for data sourcing relevant to the analytic models above.
• Technical owner/SME of the machine learning tech stack.
• Some Dashboard/report creation in PowerBI / Tableau for the tracking of key data metrics, where appropriate.
• Liaison with the Enterprise Data Management team, providing mentorship on client data analytics data assets.
• Picking up data analysis and some development tasks within a 2-week sprint, providing work estimates for tasks to project management, and participating in agile ceremonies.
• Carry out additional duties as assigned.

• 3-5 years of experience in a descriptive analytics role, such as data engineering or BI / Dashboard report development, with experience with data visualization or reporting tool such as Tableau, Power BI, Qlikview, or similar BI Tool.
• 1-3 years of experience in a data science role using tools such as R, Python, Spark, etc to develop predictive / prescriptive modeling, with experience implementing data-science related products (Recommendation Engine, Customer Segmentation, etc.).
• Strong statistical background and preferably a good knowledge of data mining techniques.
• Experience implementing Data-Science-related products (Recommendation Engine, Customer Segmentation, etc.).
• Experience with A/B or Multivariate testing.
• Must be familiar with Agile delivery methodology and have participated in the writing of user stories and all agile ceremonies.
• Financial services industry experience is a plus.

• Solid understanding of information technology methodologies and standards.
• Problem solving and analysis; understanding of complex issues and problems and able to craft pragmatic but robust solutions.
• Self-motivation; possessing an ability to take initiative and progress projects and initiatives with minimal support.
• Strong written and verbal communication and reasoning skills.
• Time management and planning; handling personal workload effectively, setting realistic and achievable targets, managing expectations and delivering to those targets.