Data Analyst

at  Maximus Health Inc

POSITION IS ON-SITE OR REMOTE (US/CANADA)

Maximus (https://www.maximustribe.com/)is a mission-driven consumer health company that provides men with content, community, and clinical support to optimize them in mind and body. Maximus has raised $15M from top Silicon Valley VCs such as Founders Fund and 8VC as well as leading angel investors/operators from companies like Bulletproof, Tinder, Coinbase, Daily Stoic, & Shopify.
Maximus is looking for a Data Analyst to drive data-driven decision-making and processes optimization across the organization. The Data Analyst will be responsible for gathering, analyzing, and interpreting data to provide actionable insights and recommendations. They will have the opportunity to work directly with department heads in operations, finance, marketing, and product.
You will be the primary point of contact for data inquiries and will collaborate closely with teams to ensure their data needs are met. You will create and maintain dashboards, generate reports, and conduct detailed analyses to support strategic initiatives and day-to-day operations.
You will work closely with data engineering, communicating data needs and their priority to ensure that the data necessary to meet the analytic needs of stakeholders is prioritized and developed into the data architecture.
The ideal candidate has a strong analytical background, excellent problem-solving skills, and the ability to communicate complex data insights clearly and effectively. They should be proficient in using data analysis and visualization tools, have a proactive attitude, and possess excellent organizational and multitasking abilities. We’re looking for someone that is focused, goal-oriented, and takes full ownership of their work. Having a track record of setting and meeting deadlines providing error-free deliverables. Someone that is a strong investigator and curious to understand data.
Please note: Culture is key at Maximus, so we get to know candidates holistically through our questionnaire. You will receive an invite in a separate email upon submitting an application. Please fill it out as honestly and intuitively as possible since it is designed to detect exaggeration, which will cause your application to be automatically rejected. The questionnaire is optional to submit now with your application, but candidates that do so will get strongly prioritized. Note, we do not have access to individual questions’ answers/choices.

REQUIREMENTS:

• Experience: 3-5 years of experience as a Data Analyst in eCommerce, preferably in a growth-stage start-up working with stakeholders from across the organization.
• Ownership & Independence: Strong sense ownership and independence throughout the analytic lifecycle, from the point of receiving the request through delivery. This includes gathering requirements, setting and meeting deadlines, identifying data needs, conducting analysis, conducting quality assurance, and ultimately delivering the analysis. Deliverables detail methodologies, limitations/considerations, and include clear recommendations based on the business problem it is intended to solve.
• Technical Skills: Proficient in SQL, BigQuery, LookerStudio, or similar data analysis and visualization tools. Strong ability to interpret and work with complex data sets. Experience in statistics and Python are a plus.
• Communication: Excellent written and verbal communication skills. Ability to clearly convey complex data insights and recommendations to non-technical stakeholders.
• Problem-Solving: Strong analytical and problem-solving skills. Ability to think abstractly and develop innovative solutions to complex problems.
• Organization: Highly organized with excellent attention to detail. Ability to manage multiple tasks and projects simultaneously.

• Data Collection and Analysis: Develop and maintain dashboards and reports to track key metrics and provide actionable insights. Gather, clean, and analyze data from various sources.
• Stakeholder Collaboration: Work closely with internal teams to understand their data needs. Clearly document deliverable requirements and host efficient working sessions as needed. Understand dependencies and expected timelines for each deliverable so that it can be prioritized and deadlines are upheld.
• Data Interpretation and Presentation: Translate data findings into clear, actionable recommendations. All dashboards and reports developed contain sufficient information (data sources used, terminology, considerations/limitations), such that a stakeholder can leverage them self-service with confidence.
• Problem Solving: Identify trends, patterns, and anomalies in data. Investigate data anomalies, first ensuring data quality, then developing actionable insights that provide stakeholders a deepening understanding of business workings.
• Quality Assurance: Ensure data accuracy and integrity by conducting regular audits and validation checks. Develop and implement processes to improve data quality. See data accuracy and reliability as a requisite for all deliverables.