Data Analyst

About the Role

QWR Interactive Solutions seeks an experienced Data Analyst with 2 to 4 years of background in hardware, manufacturing, consumer products, or technology. This candidate will own end-to-end data ownership across device production, app behavior (HUMBL), sales pipelines, and marketing performance.

Key Responsibilities

• Build and maintain executive dashboards for revenue, pipeline, production metrics, and marketing spend read weekly by the founder.
• Automate recurring reports to enable data-driven decisions without manual assembly.
• Maintain a single source of truth with documented logic ensuring consistent answers across teams.
• Analyze product and app usage (activation, retention, feature adoption) for HUMBL using tools like GA4, Firebase, or Mixpanel.
• Decode CRM pipeline data including conversion rates, cycle length, win/loss patterns, and deal stall points.
• Evaluate marketing performance across paid and organic channels focusing on CAC, cost per lead, and ROI.
• Support supply chain with yield analysis, returns, field failures, and inventory optimization.
• Translate complex business questions into actionable analyses and plain-language recommendations.
• Collaborate with engineering to ensure accurate event tracking from the source.

Required Qualifications

• Bachelor's degree in Engineering, Statistics, Economics, Computer Science or related field.
• 2-4 years of hands-on analytics experience with full ownership of outputs and queries.
• Advanced SQL skills for writing and optimizing complex queries independently.
• Working proficiency in Python or R for analysis and automation tasks.
• Fluency in at least one BI tool: Power BI, Tableau, Looker Studio, or Metabase.
• Expertise in Advanced Excel including pivots, lookups, and financial modeling.
• Familiarity with product analytics platforms such as GA4, Firebase, Mixpanel, or Amplitude.
• Demonstrated ability to explain analytical findings clearly without charts for non-technical stakeholders.

Nice to Have

• Experience in hardware manufacturing environments or consumer app ecosystems.
• Familiarity with dbt or modern data stack architectures.
• Skill in Google Tag Manager and conversion tracking implementation.
• Background in basic statistics, experiment design (A/B testing), and causal inference.