Sr. Data Product Scientist - System One
Topeka, KS 66601
About the Job
Role:
This role leads the creation, evaluation, and refinement of data-driven analytics that drive business value and enhance user experience from conception through deployment. This position is responsible for the analysis, design, development, testing and operationalization of solutions to develop insights from the data, and requires a deep understanding of BI (Business Intelligence) technics, data science expertise, AI-powered features, data product-focused thinking, cloud technologies, strong problem-solving skills, and a commitment to delivering high-quality solutions.
Responsibilities: Translate data insights into actionable insights, practical applications and an optimal user experience using machine learning, customer segmentation, and predictive analytics to uncover insights and forecast trends.
Business Problem Solving and Insight Generation: Work closely with business stakeholders to understand their needs and frame data questions and generate insights accordingly.
Analyze data (e.g., user data, market data) to identify pain points, uncover patterns, generate insights, and make recommendations to gain operational efficiencies, improve user experience & product improvements.
Work with business and technical leaders to define and prioritize data product and business analytics requirements to meet business objectives.
Conduct exploratory data analysis to identify patterns, trends, and potential new features for new business opportunities.
Stay up to date on advancements in emerging data science, AI and applying relevant methodologies to improve data services and business analytics.
Build reports and visualizations using tools like Power BI, or Python visualization libraries to present insights to product managers, engineers, and other stakeholders, ensuring data-driven decision-making.
Communicate insights, results, and recommendations to both technical and non-technical stakeholders.
Serve as a liaison between technical staff, product owners, and other business teams to translate business goals into technical specifications.
Collaborate with data engineers to deploy solutions into production, ensuring scalability, reliability, and performance in live environments.
Contribute to the data product roadmap by identifying opportunities for new data products and improvements to existing data products and data services.
Assist in establishing and evolving data governance and quality standards across data products.
Expectations: A customer-first strategic view of the job duties.
Encourage staff to expand knowledge of data driven decision making by mentoring and advising.
Anticipate future technological advances to avoid negative impact on the infrastructure and applications.
Willingness to adapt to changing business and technical environments.
Creativity and collaboration with an openness to new ideas, opportunities, and viewpoints, as well as the acceptance there is no one-size-fits-all approach.
Continuously expand skill set by learning new techniques and the willingness to share that knowledge and experience with other team members.
Contribute to data and process modernization efforts by leveraging cloud solutions and optimizing data processing workflows.
Effective communication with an understanding of stakeholders to develop strong relationships and foster collaboration.
Protect business records created or used in business processes to ensure availability, confidentiality, integrity; and retention/destruction of such as specified by relevant policies.
Ability to handle multiple tasks simultaneously, ability to problem solve, memory for details, ability to prioritize, and ability to maintain concentrated mental and visual attention for sustained periods, to meet priorities and deadlines.
Ability to showcase responsibility and dependability to set an example for team-accountability and assisting others in meeting both shared and individual goals.
Knowledge and Skills:
Experience: 5+ years of experience in Advanced Analytics, data science, machine learning, or a similar role, ideally with experience in data product-oriented data science.
Education: Four-year college degree required with emphasis in Data Science, Statistics, Engineering, Mathematics or Business preferred.
Interpersonal Skills: A significant level of trust and diplomacy is required, in addition to normal courtesy and tact. Work involves extensive personal contact with others and/or can be of a personal or sensitive nature. Work may involve motivating or influencing others.
Technical skills: Proficient in Python, R, or SQL for data analysis and model building.
Knowledge of big data processing frameworks (i.e. Spark).
Experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.
Knowledge of A/B testing, hypothesis testing, and experimentation methodologies.
Experience with data visualization tools (e.g., Power BI) Azure toolset, and experience in presenting complex insights.
Experience working in an Azure DevOps environment and supporting production operations including tools like Git.
Familiarity with Microsoft ecosystem, including Office 365, Azure, and Power Platform components.
Understanding of cloud-based data platforms (e.g., Azure) and familiarity with deploying models in production.
Experience with Agile development practices and tools (e.g., Jira, Azure DevOps)
Other Skills: Passion for data analysis and experience in storytelling using the data insights.
Understanding of principles of data engineering, including data wrangling/transformation, tools or programming languages, and data visualization/BI technologies for the purposes of identifying data insights from large data sets.
Ability to discuss technical issues effectively with other data processing professionals, technical teams as well as non-technical stakeholders.
Demonstrated abilities in problem solving, root cause analysis and ability to independently identify solutions.
Ability to think orderly, logically, and analytically showcasing strong problem-solving skills.
Ability to work and travel independently and use general office equipment, give speeches, and make presentations.
Must be goal-oriented and have a strong sense of team solidarity.
Ability to work independently and with other professionals.
Ability to work with IT leadership to help establish emergent processes and procedures to help enable the success of Data Management and Advanced Analytics.
#LI-JM4
This role leads the creation, evaluation, and refinement of data-driven analytics that drive business value and enhance user experience from conception through deployment. This position is responsible for the analysis, design, development, testing and operationalization of solutions to develop insights from the data, and requires a deep understanding of BI (Business Intelligence) technics, data science expertise, AI-powered features, data product-focused thinking, cloud technologies, strong problem-solving skills, and a commitment to delivering high-quality solutions.
Responsibilities: Translate data insights into actionable insights, practical applications and an optimal user experience using machine learning, customer segmentation, and predictive analytics to uncover insights and forecast trends.
Business Problem Solving and Insight Generation: Work closely with business stakeholders to understand their needs and frame data questions and generate insights accordingly.
Analyze data (e.g., user data, market data) to identify pain points, uncover patterns, generate insights, and make recommendations to gain operational efficiencies, improve user experience & product improvements.
Work with business and technical leaders to define and prioritize data product and business analytics requirements to meet business objectives.
Conduct exploratory data analysis to identify patterns, trends, and potential new features for new business opportunities.
Stay up to date on advancements in emerging data science, AI and applying relevant methodologies to improve data services and business analytics.
Build reports and visualizations using tools like Power BI, or Python visualization libraries to present insights to product managers, engineers, and other stakeholders, ensuring data-driven decision-making.
Communicate insights, results, and recommendations to both technical and non-technical stakeholders.
Serve as a liaison between technical staff, product owners, and other business teams to translate business goals into technical specifications.
Collaborate with data engineers to deploy solutions into production, ensuring scalability, reliability, and performance in live environments.
Contribute to the data product roadmap by identifying opportunities for new data products and improvements to existing data products and data services.
Assist in establishing and evolving data governance and quality standards across data products.
Expectations: A customer-first strategic view of the job duties.
Encourage staff to expand knowledge of data driven decision making by mentoring and advising.
Anticipate future technological advances to avoid negative impact on the infrastructure and applications.
Willingness to adapt to changing business and technical environments.
Creativity and collaboration with an openness to new ideas, opportunities, and viewpoints, as well as the acceptance there is no one-size-fits-all approach.
Continuously expand skill set by learning new techniques and the willingness to share that knowledge and experience with other team members.
Contribute to data and process modernization efforts by leveraging cloud solutions and optimizing data processing workflows.
Effective communication with an understanding of stakeholders to develop strong relationships and foster collaboration.
Protect business records created or used in business processes to ensure availability, confidentiality, integrity; and retention/destruction of such as specified by relevant policies.
Ability to handle multiple tasks simultaneously, ability to problem solve, memory for details, ability to prioritize, and ability to maintain concentrated mental and visual attention for sustained periods, to meet priorities and deadlines.
Ability to showcase responsibility and dependability to set an example for team-accountability and assisting others in meeting both shared and individual goals.
Knowledge and Skills:
Experience: 5+ years of experience in Advanced Analytics, data science, machine learning, or a similar role, ideally with experience in data product-oriented data science.
Education: Four-year college degree required with emphasis in Data Science, Statistics, Engineering, Mathematics or Business preferred.
Interpersonal Skills: A significant level of trust and diplomacy is required, in addition to normal courtesy and tact. Work involves extensive personal contact with others and/or can be of a personal or sensitive nature. Work may involve motivating or influencing others.
Technical skills: Proficient in Python, R, or SQL for data analysis and model building.
Knowledge of big data processing frameworks (i.e. Spark).
Experience with machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.
Knowledge of A/B testing, hypothesis testing, and experimentation methodologies.
Experience with data visualization tools (e.g., Power BI) Azure toolset, and experience in presenting complex insights.
Experience working in an Azure DevOps environment and supporting production operations including tools like Git.
Familiarity with Microsoft ecosystem, including Office 365, Azure, and Power Platform components.
Understanding of cloud-based data platforms (e.g., Azure) and familiarity with deploying models in production.
Experience with Agile development practices and tools (e.g., Jira, Azure DevOps)
Other Skills: Passion for data analysis and experience in storytelling using the data insights.
Understanding of principles of data engineering, including data wrangling/transformation, tools or programming languages, and data visualization/BI technologies for the purposes of identifying data insights from large data sets.
Ability to discuss technical issues effectively with other data processing professionals, technical teams as well as non-technical stakeholders.
Demonstrated abilities in problem solving, root cause analysis and ability to independently identify solutions.
Ability to think orderly, logically, and analytically showcasing strong problem-solving skills.
Ability to work and travel independently and use general office equipment, give speeches, and make presentations.
Must be goal-oriented and have a strong sense of team solidarity.
Ability to work independently and with other professionals.
Ability to work with IT leadership to help establish emergent processes and procedures to help enable the success of Data Management and Advanced Analytics.
#LI-JM4
Source : System One