Data Analyst
Goebel Fixture Company
- Helena, Montana, United States
- Helena, Montana, United States
About
Employee Type Full Time Exempt
About Us:
We are a fast-growing U.S.-based manufacturing company that designs, produces, and sells high-quality consumer products exclusively through our own direct-to-consumer digital channels. By owning the full vertical—from manufacturing to customer delivery—we deliver exceptional value, rapid innovation, personalized experience, and strong profitability to our loyal customer base. We’re seeking a sharp, business-oriented Data Analyst passionate about transforming data into insights that fuel revenue growth, optimize marketing efficiency, enhance manufacturing operations, and strengthen financial health—including profitability, unit economics, and cash flow management.
Position Overview The Data Analyst will be a key player in our data-driven culture, partnering across Marketing, E-commerce, Product, Supply Chain, Manufacturing, and Finance teams. You will collect, clean, analyze, and visualize data from end-to-end operations to answer critical business questions, uncover opportunities, and support strategic decisions around growth, efficiency, and financial performance. This high-impact, cross-functional role bridges operations, customer experience, and finance in a vertically integrated DTC manufacturing environment.
Key Responsibilities
Collaborate with Marketing, E-commerce, Product, Supply Chain, Manufacturing, and Finance teams to translate business priorities into analytical frameworks and questions
Build and maintain executive-level dashboards and reports covering customer metrics (acquisition, LTV, retention, repeat behavior), operational KPIs (yield, efficiency, inventory turns), and core financial metrics (gross margin, contribution margin, COGS per unit, unit economics, cash conversion cycle)
Conduct deep-dive analyses to identify trends, diagnose issues, and pinpoint opportunities in revenue, profitability, cost control, and cash flow
Own customer segmentation, cohort analysis, lifetime value modeling, and unit economics analysis (LTV:CAC, contribution margin by product/channel, break-even analysis) to guide acquisition, retention, and pricing strategies
Evaluate marketing performance (ROAS, CAC, incrementality, blended efficiency) across paid social, email/SMS, SEO, affiliates, and new channels
Support merchandising, product development, and financial planning with sales trend analysis, attribute performance, inventory forecasting, gross margin by product/SKU, COGS variance analysis, and contribution margin optimization
Track and analyze manufacturing & operational KPIs (production efficiency, quality metrics, cost per unit, capacity utilization, scrap/waste rates, inventory turnover)
Monitor key financial health indicators including gross profit margin, contribution margin per unit, operating profit trends, and cash-to-cash cycle
Design, execute, and analyze A/B and multivariate tests for website features, email campaigns, advertising creative, promotions, and pricing strategies
Identify data gaps and quality issues; partner with engineering, operations, and finance teams to enhance data collection and integrity
Present clear, compelling, visual insights and actionable recommendations to stakeholders at all levels, including executive leadership and finance teams
Required Qualifications
Bachelor’s degree in Analytics, Statistics, Economics, Finance, Business, Industrial Engineering, Supply Chain, or a related quantitative field
2–5 years of hands-on experience as a Data Analyst (DTC/e-commerce, consumer products, manufacturing, or finance-related analytics strongly preferred)
Strong proficiency in SQL (required) for querying large, complex datasets
Advanced Excel skills (pivot tables, dynamic arrays, Power Query, financial modeling)
Experience building interactive dashboards in Looker, Tableau, Power BI, or Google Looker Studio
Familiarity with digital analytics tools (Google Analytics 4, Shopify Analytics, Klaviyo, Triple Whale, Northbeam, etc.)
Solid grasp of statistical methods, A/B testing, and basic financial concepts (margins, unit economics, ROI)
Excellent communication & storytelling skills — able to translate complex data into clear, business-impactful recommendations
Preferred Qualifications
Experience with Python or R for advanced data manipulation and modeling
Knowledge of cloud data warehouses (Snowflake, BigQuery, Redshift)
Prior work with DTC financial frameworks (LTV:CAC ratios, contribution margin modeling, blended ROAS, gross margin optimization)
Exposure to manufacturing/operations data (ERP/MES systems, COGS tracking, variance analysis)
Familiarity with marketing mix modeling, incrementality testing, or financial forecasting
Benefits
Full-time position
Paid Vacation
401k Matching
Medical
Vision
Health Savings Account (HSA) and Dependent Care Flexible Spending Account (DCFSA)
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Languages
- English
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