• 39041
  • Non-Life - Data Science
  • |
  • New York, United States
  • |
  • Feb 4, 2021
  • Run technology agile ceremonies including daily stand-ups, (bi-)weekly sprints and retrospectives in a co-leadership role with the senior technologist lead.
  • Produce documentation for a quarter planning process, executive roadmap updates, product requirement documents and provide continual feedback for improving product process.
  • Gather stakeholder requirements and user feedback for creating and prioritizing epics and story level tickets in our agile project management system.
  • Participate in or lead the full product lifecycle for designated product areas, including research, scoping, prototyping, validation, productizing, and rollout. This includes management of blockers, dependencies, and risk factors across engineers, data scientists and analysts.
  • Ownership of end-to-end product delivery including documentation, training, communication, and mediating expectations of users and stakeholders.
  • Measure product and operational key performance indicators such as user engagement metrics or engineering velocity and regularly presenting leadership.
  • Understand the key value drivers for your product areas and demonstrate progress against success metrics to ensure our products are delivering value as expected.
  • Maintain a high-level understanding of the underlying technical components in product solutions to converse with internal team members and external parties on where key issues or risks may reside and performing product improvement estimation.
  • Build an evolving awareness of the capabilities and limitations of data technologies such as data lakes, operational databases, backend APIs, distributed computing (e.g. Spark), crowd sourcing, scripting and data access languages (e.g. SQL) and how they relate to business outcomes.
  • Contribute and/or provide feedback on overall data strategy or other product team initiatives such as data acquisition roadmaps, entity resolution, data cataloging and the lake ontology.
  • 5+ years of professional work experience
  • 2+ years of experience in a product management role, preferably at a data company
  • Bachelor’s degree required preferably in a quantitative discipline such as computer science, engineering, mathematics or physics
  • Experienced in and enthusiastic about working with data in a variety of manners spanning proficiencies in Excel, SQL, API requests and basic scripting in Python or R
  • Strong familiarity with agile development principles
  • Excellent communication skills. Must be comfortable talking with technologists, stakeholders, clients and executives, both in-person and remotely. Write clearly and succinctly. Listen well.
  • Conversant about technology and able to understand the effort required to deliver enterprise grade platforms, with a focus on data quality
  • Comfortable working at a high level, as well as down to the lowest levels including writing JIRA tickets and providing support as necessary Leadership skills, client-facing experience, and the ability to influence and partner with internal and external stakeholders Experience with documentation management and maintenance
  • Experience with cloud technologies such as AWS / Google Cloud / Microsoft Azure
  • Familiarity with Spark concepts such as SparkSQL, dataframes, RDDs and cluster management
  • Knowledge of data science platforms such as Databricks and DataRobot
  • Exposure to citizen data preparation tools such as Trifacta, Paxata or Alteryx