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Data Analyst

San Francisco, CA (On-site)

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As a Data Analyst, you will turn data into insights that guide decision-making both within Methodic and for our clients. Our platform generates a wealth of data – transaction volumes, user behavior patterns, system performance metrics, etc. – and our business has its own operational data. You’ll be responsible for analyzing these and helping the team understand trends, measure success, and identify opportunities for improvement or growth. Your work will ensure we remain a data-driven organization, continually tuning our efforts based on what the numbers tell us.

Responsibilities

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Define and track key performance indicators (KPIs) for both the product and the business. This might include metrics like number of active accounts on Methodic, transaction throughput per client, uptime percentages, customer acquisition cost, retention rates, and so on.

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Build and maintain dashboards and reports that provide visibility into these metrics for stakeholders (e.g., a dashboard for the leadership team showing monthly new accounts and revenue, or a dashboard for the product team showing feature usage stats and system load).

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Perform exploratory data analysis to answer specific questions as they arise – for example, “Which features of our platform are used most heavily by trading app clients vs. savings account clients?” or “Is there a correlation between how quickly a client completes onboarding and their success on our platform later on?”.

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Analyze customer usage patterns and feedback data to help identify where customers might be struggling (e.g., if many customers drop off at a certain step, or frequently ask for a certain feature).

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Work with the marketing team to analyze the effectiveness of campaigns and channels (e.g., conversion rates from different marketing sources, characteristics of leads that convert vs. those that don’t).

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Provide data-driven insights to support strategic decisions (for example, if considering entering support for a new country, help estimate market size and potential impact based on data).

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Ensure data accuracy and integrity by working with engineering to log the right events and by routinely checking for anomalies or inconsistencies in the data.

Requirements

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3+ years of experience in data analytics, business intelligence, or a related role.

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Proficiency in SQL for querying databases and extracting data; experience with data analysis in Python or R is a plus.

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Familiarity with data visualization and BI tools (such as Tableau, Power BI, Looker, or even building dashboards using Python libraries) to create understandable reports and visuals.

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Strong analytical thinking and statistical knowledge – able to interpret data trends, conduct basic statistical analyses, and avoid common pitfalls/misinterpretations.

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Experience working with SaaS or product usage data is helpful (understanding concepts like user cohorts, funnel analysis, churn, etc.).

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Ability to communicate insights clearly, both in writing (documentation, reports) and verbally (presenting findings to the team), tailoring the depth of detail to the audience.

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Curiosity and a problem-solving attitude – you love digging into data to uncover the story it’s telling, and you’re proactive in seeking out new analyses that can benefit the company.

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Data Analyst

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