Senior Data Analyst

Come work with us to do what you love and stay for the Frontier TRACK …

• Team Centric
  :
  We each take responsibility for fostering an environment of personal and professional growth. We are eager to help, support and collaborate with one another recognizing that we are better when we work together.
• Respectful and Inclusive
  :
  We treat everyone the way we want to be treated and accept everyone on the team just as they are.
• Autonomous and Accountable
  :
  We are entrusted with and given the space to do our work and in turn hold ourselves accountable for results.
• Committed to Excellence
  :
  We are fueled by the desire to be our best and to make an impact now and tomorrow.
• Keep it Real
  :
  We lead with integrity and genuineness in our work, interactions and relationships.

We're looking for a hands-on Senior Data Analyst who will own our end-to-end analytics process – from data collection and preparation to insight delivery – turning raw data into actionable strategies that improve customer retention and drive business growth.

Key Responsibilities
:

Sales & Business Insights

• ML/AI
  – Apply machine learning and AI to accelerate decision-making and identify opportunities for increased revenue: customer segmentation, churn/retention propensity, next-best-offer and promo uplift modeling, demand/forecast refinement, price elasticity insights, and anomaly detection for sales operations.
• Insight generation
  – Analyze sales trends, customer behavior, and market data to identify opportunities for increased revenue.
• Campaign analysis
  – Evaluate the performance of marketing campaigns and promotional initiatives, providing data-driven recommendations to maximize ROI and customer engagement.
• Forecasting & strategy
  – Partner with sales and marketing leadership to develop data-informed sales forecasts, pipeline analyses, and pricing strategies that drive growth and operational efficiency.
• Cross-functional collaborator
  – Work closely with teams across the organization (sales, marketing, purchasing, etc.) to understand business needs, manage stakeholder expectations, and ensure that insights are translated into actionable business decisions.

Data Analysis & Reporting

• Data wrangler
  – Leverage data from multiple sources (e.g. ERP, CRM, web analytics, etc.) to create a single source of truth for analysis.
• Dashboard & reporting
  – Design and maintain interactive dashboards and reports (using tools like Power BI or similar) to monitor key performance indicators and communicate trends to stakeholders in real time.
• Pipeline automation
  – Develop and automate reliable ETL/ELT workflows using SQL and Python scripts to ensure timely availability of accurate data for analysis.
• Data quality & governance
  – Implement data validation checks, documentation, and version control to uphold data integrity, security, and compliance with governance standards.

Technical Skills:

• Experience:
  5+ years in data analysis, business intelligence, or a related analytics field, preferably in a fast-paced or high-growth ecommerce environment.
• End-to-end analytics:
  Demonstrated success owning analytics projects from start to finish – from gathering business requirements and extracting data to building dashboards and presenting insights that influenced key decisions.
• Ecommerce domain knowledge:
  Proven experience working with sales and customer data to produce insights that improved customer retention, guided revenue growth, or informed successful sales/marketing strategies.
• SQL & Python:
  Expertise in writing complex SQL queries for data extraction and transformation, along with proficiency in Python for data analysis and automation (e.g. using pandas, NumPy, or scripting ETL workflows and other statistical libraries).
• Data visualization:
  Hands-on experience with modern BI tools, especially
  Power BI
  (or similar platforms like Tableau/Looker), to create interactive dashboards and reports. Ability to craft insightful data visualizations and DAX measures (if using Power BI) is a strong plus.
• Data ecosystem:
  Familiarity with cloud-based data warehouses and tools (AWS, Azure, or GCP ecosystems) and comfort working with large datasets. Knowledge of data modeling and data pipeline frameworks (dbt, Airflow, etc.) is advantageous.
• Strategic mindset:
  Ability to translate high-level business objectives into analytical questions, and to interpret data findings in the context of business strategy. Demonstrated skill in communicating actionable recommendations to both technical and non-technical stakeholders.

While experience with the tools listed is a plus, we strongly encourage applicants with expertise in comparable technologies to apply. Relevant industry certifications are a plus – for example, AWS or Azure cloud certifications, or data platform certifications like Fabric, Snowflakes or Databricks.