Product Data Scientist

New York, US, NY

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Celonis

The Celonis Process Intelligence Platform — powered by process mining — lets you reveal and realize the value opportunities hiding in your business processes - fast. Get started quickly and scale infinitely.

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We're Celonis, the global leader in execution management and process mining technology, and one of the 50 most valuable private companies in the world. We believe that every company can unlock its full execution capacity - and for that, we need you to join us as a Product Data Scientist.

The Team:

As a member of the Engineering organization, the  Product Analytics & Data Sciences team provides analytic support and a strategic perspective to the product and engineering teams to enable them to make evidence-based decisions. We deliver actionable insights by collecting, organizing and interpreting data about user journeys, product telemetry, incidents, infrastructure utilization, sales motions, and much more. We transform data into analytic assets by conducting exploratory analysis, identifying outliers, validating hypotheses, building statistical models, quantifying risk; communicating findings through well crafted stories and critical recommendations.

The Role:

As a Product Data Scientist in the Product Analytics & Data Sciences team, you will play a key role in developing and communicating data-driven insights that will help with strategic and tactical decision making in a hyper growth environment. You will partner with engineers and product team members to understand business problems and help define data solutions. You will build data pipelines for new data sources, develop machine learning models and create visualizations to communicate findings and recommendations to engineers, managers and executives. In this exciting role, in addition to crunching data, you will also need to facilitate data driven discussions between stakeholders across the organization, through effective storytelling with meaningful insight.

The work you’ll do:

  • Serve as the data science specialist on the team, building data-driven insights to deliver findings and recommendations to product and engineering teams
  • Build visualizations as well as written narratives to communicate quantitative insights and facilitate discussions with data driven insights.
  • Employ statistical analysis and/or modeling techniques on a variety of data  - product telemetry, incidents, user journeys, sales motions, infrastructure utilization and others, to drive resource optimization, feature improvement or product adoption related initiatives
  • Collaborate with partners across the product and engineering teams to understand business motivations; formulate and deliver data analysis by engaging across all the steps of the process, including data gathering, building data pipelines, performing analyses and delivering insights at scale 
  • Continuously engage in refining data engineering processes to ensure data accuracy, consistency, and integrity through continuous audit and review.
  • Effectively present and communicate analytical findings to stakeholders across the organization.

The qualifications you need:

  • Bachelor’s degree or equivalent with a strong focus on Mathematics, Computer Science, or Data Science. Master’s preferred.
  • 3+ years relevant experience as a Product Analytics Engineer / Data Scientist or similar, partnering with product, engineering or growth teams 
  • Technical competence with analytical tools for data extraction, visualization and analysis (SQL, Python, Pandas)
  • Strong understanding of statistical techniques and machine learning
  • Experience working with large datasets and predictive modeling
  • Outcome-oriented with strong decision-making skills and the ability to prioritize multiple objectives while meeting aggressive deadlines
  • Have excellent written and verbal communication skills; exceptional attention to detail
  • Experience working in agile teams using collaboration software like Jira or similar
  • Eager to work in a fast-growing organization with diverse and international teams spread across multiple locations

What Celonis can offer you:

  • The unique opportunity to work within a new category of technology, Execution Management
  • Investment in your personal growth and skill development (clear career paths, internal mobility opportunities, mentorships, yearly development stipend)
  • Great compensation and benefits packages (stock options, 401(K) matching, generous time off, parental leave, and more)
  • Work from home support (mindfulness tools such as Headspace, monthly remote working stipend, flexible working hours, virtual events and workshops)
  • A global and growing team of Celonauts from diverse backgrounds to learn from and work with
  • An open-minded culture with innovative, autonomous teams
  • Employee resource communities to help you feel connected, valued and seen (Women@Celonis, Parents@Celonis, Pride@Celonis, Resilience@Celonis, and more)
  • A clear set of company values that guide everything we do: Live for Customer Value, The Best Team Wins, We Own It, and Earth Is Our Future

About Us

Celonis believes that every company can unlock its full execution capacity. Powered by its market-leading process mining core, the Celonis Execution Management System provides a set of applications, and developer studio and platform capabilities for business executives and users to eliminate billions in corporate inefficiencies. Celonis has thousands of global customers and is headquartered in Munich, Germany and New York City, USA with 15 offices worldwide.

Celonis is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Different makes us better

Tags: Agile Computer Science Data analysis Data pipelines Engineering Jira Machine Learning Mathematics ML models Pandas Pipelines Predictive modeling Python SQL Statistics

Perks/benefits: Career development Equity Flex hours Flex vacation Home office stipend Parental leave Team events

Region: North America
Country: United States
Job stats:  10  2  0

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