Data Analyst
Job description
About the role
The will own the transformation of datasets from a consumer health platform into strategic options that directly guide business decisions. You will collaborate closely with growth and operations teams to convert complex information into actionable guidance for the client, ensuring that data insights drive tangible outcomes. This role requires you to turn raw health data into clear narratives that influence strategic direction and operational improvements. You will be responsible for maintaining the integrity of the analysis process while enabling self-service capabilities for stakeholders. The work involves close coordination with business teams to align data initiatives with organizational goals. Your expertise will help translate physiological insights from biomarker data into personalized guidance delivered through a mobile app. Ultimately, this position focuses on empowering decision-makers with reliable, high-quality data analysis.
Key facts
What you'll do
Purpose: ensure data quality and self-service analysis through rigorous validation and monitoring of datasets. Purpose: provide clear, data-driven guidance to stakeholders by synthesizing complex health data into understandable insights. Conduct independent querying and validation of data to ensure accuracy and reliability without requiring engineering support. Build and maintain dashboards using BI tools such as Omni, Looker, Metabase, or Tableau to drive data-informed decisions. Implement and leverage data stack practices and dbt methodologies to facilitate smooth collaboration with data and engineering teams. Design and execute analyses that uncover trends and patterns in consumer health behavior derived from hormone and biomarker data. Develop metrics and frameworks to interpret physiological insights and translate them into personalized user guidance. Partner with growth and operations teams to integrate data findings into strategic planning and product optimization. Perform statistical analysis to support experiments and interpret results within the context of consumer health outcomes. Document methodologies and insights to create a reusable knowledge base for ongoing analysis and decision support.
Requirements
A bachelor's degree in a stated field is required; The role demands 3 to 5 or more years of experience in analytics-focused roles within relevant industries. Professionals must perform independent querying and validation to ensure data quality without engineering support. Candidates need to build dashboards that drive decisions using at least one BI tool such as Omni, Looker, Metabase, or Tableau. Knowledge of dbt and data stack practices is necessary to support smooth collaboration with data and engineering colleagues. A strong portfolio of past analyses is emphasized as more important than degrees in many hiring decisions. The position requires years of experience working with data tools and methodologies. Only candidates with demonstrated ability in data analysis will be considered for this role.
Nice to have
There are no preferred items specified in the source for this role.
Practical notes
Some companies give a take-home analysis. Typical interview steps include data interviews that commonly feature a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model as part of the evaluation process. Some companies provide a take-home analysis to further assess practical skills. Expect questions regarding past projects and the business impact of your work during interviews. Interviewers often evaluate how candidates communicate uncertainty and business impact, not only mathematical correctness. Bringing a clean write-up of a past analysis to the interview is well received and can demonstrate your analytical communication skills.
Good to know
Data specialists turn complex measurements into decisions by transforming raw data into actionable insights. Modern data teams rely on version control and automated testing for reliable pipelines to ensure data integrity. Strong storytelling with numbers is essential to help non-technical stakeholders understand results and make informed decisions.
Questions to ask
It is worthwhile to ask in any interview how the team measures success and what key performance indicators are used to evaluate outcomes. Understanding who the role works with daily provides insight into collaboration expectations and team dynamics. Clarifying what the onboarding looks like helps candidates prepare for a smooth transition into the position. Inquiring about what the company is trying to achieve this year aligns your goals with organizational priorities. Asking what past hires did well is a strong final question that reveals team expectations and cultural fit. Keep the list of questions short and select the questions that matter most to your decision-making process.
Career growth
Data careers grow toward senior analyst positions, staff data scientist roles, or data engineering leadership positions. Many professionals choose to specialize in areas such as machine learning, analytics, or infrastructure as they progress in their careers. Cross-functional work with product and engineering teams becomes increasingly important at senior levels of responsibility. The field changes quickly, making continuous learning an integral part of the job. Professionals who can translate numbers into decisions tend to advance faster in their careers.
About the company
Fitt Talent Partners is a specialized recruitment firm working with top health and wellness companies. We're filling this role for a client building a consumer health platform that measures and interprets hormone and biomarker data, translating complex physiological insights into personalized guidance through a mobile app designed to help people better understand and take action on their health. The company focuses on leveraging data to improve consumer health outcomes and provide users with meaningful guidance based on their biological data. This role represents an opportunity to contribute to a modern health platform that prioritizes data-driven decision making.