Product Analyst

You Will:

• Enable product teams to define the right metrics for measuring the success/performance of the product they are responsible for.
• Guide the teams to define these metrics along the lines of standardized metrics we use across the entire platform.
• Identify, together with the product manager, development team and ideally a UX designer, which signals/events/datapoints are required to calculate the metric(s).
• Bring in your cross-platform expertise, to add extra attributes to these triggers/events so reusability of the data point is maximized across the platform.
• Support the development teams during implementation of the event with questions regarding, timing, attributes, etc.  
• Test the implemented events for correctness, before the switch over to production is made.
• Execute exploratory analysis on the newly ingested datapoints and align with our analytics data engineer, how these datapoints are best added into our standardized data model.
• Build the rough queries with the required transformations for this (building up the knowledge and requirements, developed during the previous phases) and hand these over to the analytics data engineers for production and improvements of those queries.

Activities You Can Expect to Work On:

• Scope and challenge analytics requests from the business.
• Brainstorm new product feature ideas with product managers, designers, developers and leadership teams.
• Help the business define, create and operationalize their metrics and KPIs.
• Build operational and management level dashboards in Power BI.
• Retrieve & transform data using SQL (and/or Python/R).
• Support the data engineer in our team in creating the right pipelines and data structures for new and existing data.
• Design and conduct in-depth research with large, raw, datasets.
• Apply statistical techniques to metrics and hypotheses to prove significance of results & present your findings and actionable recommendations or analytics products to the business.
• Create enablement strategies for analytics products.
• Grow your skills by learning from other analysts, and drive collaboration by sharing your knowledge and experience.

Data & Analytics Requirements:

• PowerBI: Experience designing, building and deploying production grade PowerBI reports. Working knowledge of DAX. Experience distributing reports/insights through the PowerBI service, to a diverse set of users in a controlled and governed manner.
• SQL: Experience building efficient queries(for large datasets), running script tests/validations, and preparing data ready for your analysis/dashboard/model.
• Data modeling & Pipelines: Experience selecting, designing and building efficient data models for the analytics task at hand. Experience building the individual pipeline steps/components required to validate, monitor, clean and transform the raw data into your target data model (we have an analytics data engineer to harden/productionize/integrate these steps), And, experience defining requirements for data capturing in the data lake and making sure data is organized and cleaned.
• Python: Experience creating scripts for data processing and/or (advanced) analytics purposes, and ensuring scripts are reliable and deliver reproduceable results.
• Statistics: Strong understanding of statistical concepts and the ability to explain these concepts to stakeholders, as well as how to apply these concepts in daily delivery of data products for reliable and statistically proven insights ready to be used for decision making.
• Other: Possess strong numerical and analytical skills. Capable of defining, creating, setting targets, forecasting and operationalizing KPIs and/or OKR structures. Ability to bring a data & analytics project to success, from begin to end, from research/hypothesis testing, exploratory data analysis, converging towards conclusions, presenting those to stakeholders. Have the means to efficiently document your work, code, scripts, etc. for reusability. Experienced with git version control workflows (including Pull Requests and Code Reviews).

Business Requirements:

• Ability to present actionable insights from research to management and high-level executives in a non-technical and appealing way.
• Experience advocating data literacy among the entire organization.
• Competency in gathering requirements from non-data professional stakeholders.
• Aptitude to challenge stakeholders in order to uncover the right requirements and clearly scope requests.
• Wherewithal to familiarize yourself with different business domains and (technical) features on the platform.
• Previous display of stakeholder management between various business units and management levels.
• Experience mentoring colleagues & stakeholders.

Bonus:

• You have a solid understanding of AI/Machine Learning concepts and being able to identify opportunities where AI/ML can make the difference, and experience building, training, validating, deploying and monitoring these models in production environments.
• You have technical knowledge and/or experience with:  AWS Services like Athena, AWS Glue, etc..., Linux/CLI, Bash Scripting & Docker and/or Kubernetes.
• You are familiar with Low Code development.
• And lastly, product-led growth is a plus!

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If you see a job description and think, “I’d be perfect for that” but your experience doesn’t align perfectly with the qualifications – don’t let that hold you back. We’re always eager to hire talented, passionate candidates – so give it a try and apply.

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