Data Analyst

Who we're looking for?

Are you able to review and understand data, analyze it, and present conclusions and insights from the data?  Are you not only strong in analytics, but also think broadly and understand broad concepts like business, markets, finances, and trends?  Are you able to analyze and present patterns of revenue/profit, business trends, or product usage data?  If so, this is a great opportunity for you!  We are seeking a candidate with a passion for analytics in business, product management, or as a data scientist.

What’s the work like?

We build cutting-edge Cloud-based software applications which are used by over 15,000 companies around the world, predominantly in the US, Australia, and Canada. Our goal is to be the leading SaaS provider for enterprises around the globe. Our customers include NASA, 3M, Disney, Amazon, and many others. We seek to be intelligence-driven, by using the data we have to understand our customers better and make deep decisions.

You would play a central role in the exciting space of data intelligence and analytics by being:

1. Energetic and enthusiastic about insights, intelligence, and decisions based on data
2. Having a quest to “find the truth”
3. Excellent listening ability, confidence to ask questions and derive answers
4. Strong communication skills to convey your findings and good interpersonal skills
5. Ability to work independently
6. Quick learner when it comes to grasping technical and business-related concepts

Responsibilities

• Analysis Projects: Each of our main apps has new features to evaluate, hypotheses to validate, and decisions to be made. Each set of insights needed would be an Analysis Project.  You would work with stakeholders to understand the insight needs, and then conduct the project from gathering the data to analyzing the data, to presenting the findings.
• Problem Solving: A key part of every project is to go from goals and needs to determine how you would use analytics to solve the problems given.  For example, how can we increase the rate of sign-ups for a new feature?  You would determine what the analytics are to solve that problem.
• Tagging Data: Based on the requirements of feature analysis, tag the appropriate actions inside Google Analytics, to get intelligence from click-stream data.
• Assimilating Data: The data will be available inside different apps or tools, and you would pull it into one spreadsheet or data tool for you to analyze.
• Creating New Hypothesis and Insights:  Outside of known projects, you would determine your own questions about what is critical for insights - and how to find the insights for it.
• Direction and Strategy: Based on the insights you have created, you would advise on the strategy and direction of our products.
• Systems Improvement: Determine improvements in our process and systems that are used to gather and analyze data.
• Machine Learning Features: You would also have the opportunity to work on machine learning, working closely with product managers, to build features in our product.  For example, building software features so our customers get incredible insights that help them make better decisions in their business.

Key Activities:

Your typical day will be spent in these activities:

1. Meeting with product teams to engage in defining strategy, goals of features and hypothesis and approach to problem-solving for the goals given
2. Problem-solving and forming approaches to get at the answer needs; and then applying analytical techniques on data in order to get to the right measures and insights
3. Performing regular updates on outcomes of strategies and features - so that the progress is tracked along a timeline, and we adjust our strategy as we go
4. Lifting up any ambiguities or blockers to solve on your own, or bring to the team to resolve, so that progress keeps going forward
5. Innovating ways to automate reporting, analysis, and data models.  This includes using dashboards and reporting software to be available to product teams
6. Working on machine learning approaches and features in our products
7. Communicating insights and decisions across the team and senior stakeholders

Requirements:

1. 5+ years of experience in an analytical role, whether in the field of business, finance, software product, or data analysis and machine learning
2. Basic understanding of clickstream data created by online software applications, such as Google Analytics
3. Hands-on experience in using Excel or Google Sheets to do advanced analysis and reporting
4. Business intelligence, dashboard creation, and data model creation experience
5. Bachelor’s Degree in Business or Finance (with an emphasis in analytics), Computer Science, or Data Analytics/Data Science is required.

Nice to have but not required:

• Current Tools that we use for Data Insights:  Internal Product Data, Google Analytics, Datadog, Zoho CRM, Zendesk, Hotjar
• Solutions we are exploring:  Pendo, MixPanel, Amplitude, Open to suggestions