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We Sell Cellular LLC

Data Scientist

We Sell Cellular LLC, West Islip, New York, United States

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This range is provided by We Sell Cellular LLC. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range $75,000.00/yr - $105,000.00/yr

Additional compensation types Annual Bonus

Employment Type Full-time

Position Overview We Sell Cellular (WSC) is a leading U.S.-based distributor of used smartphones. To further strengthen our competitiveness in pricing, inventory efficiency, and operational performance, we are looking for a Data Scientist who will focus on data-driven pricing strategy, inventory optimization and KPI improvement, especially around DIO (Days Inventory Outstanding), margin performance, and sales velocity.

In this role, you will work closely with Sales, Purchasing, Operations, and our warehouse teams to analyze sales and inventory data, develop price-related models, and build dashboards that directly support business decision‑making. Your work will have a direct and measurable impact on WSC’s performance.

Key Responsibilities

Analyze sales patterns, pricing trends, and device-level demand behavior

Visualize and monitor key business KPIs such as DIO, margin, and sales velocity

Identify optimal pricing ranges based on historical sales and inventory data

Provide data-based recommendations for price adjustments and inventory actions

Collaborate with Sales and Purchasing on pricing strategies and decision‑making

Modeling & Forecasting

Build and maintain pricing models (regression, time‑series, predictive models)

Estimate demand fluctuations caused by seasonality, device cycles, and market events

Develop early‑warning logic for slow‑moving or overstocked inventory

Improve pricing recommendation logic for new incoming stock

Collaboration with the DWH Team

Define data requirements for sales, inventory, and operational analytics

Support data modeling and ensure high‑quality, analysis‑ready datasets

Work closely with Operations and Quality teams to improve data collection and accuracy

Contribute to the integration of multiple data sources into a unified DWH structure

Build dashboards using Looker / Looker Studio for Sales, Purchasing, and Management

Develop weekly and monthly performance reports for the leadership team

Maintain monitoring tools and anomaly alerts for key pricing and inventory indicators

Support the creation of pricing dashboards used in daily operations

Cross-Functional Collaboration

Work closely with Sales, Purchasing, and Operations to translate analysis into actions

Conduct periodic on-site coordination with warehouse teams to understand operational data

Support ad‑hoc analysis for business partners in Japan (Japanese language skills are welcomed)

Required Qualifications

Practical experience with Python (Pandas, NumPy, scikit‑learn)

Strong SQL skills for data extraction and transformation

Solid understanding of statistical methods (regression, time series, hypothesis testing)

Experience with BI tools such as Looker, Looker Studio, or Tableau

Proven ability to link data analysis to KPI improvement and business outcomes

Experience collaborating with non‑technical teams (Sales, Purchasing, Operations)

Hands‑on experience working with multiple data sources and ensuring data quality

Preferred Qualifications

Experience in pricing analytics, demand forecasting, or revenue optimization

Experience working in DWH environments (BigQuery preferred)

Experience using ELT tools such as dbt or Dataform

Experience analyzing data from supply chain, distribution, retail, or inventory-driven businesses

Experience building Machine Learning models and MLOps eco‑system

Familiarity with WMS (Warehouse Management System) data

Experience using AI/LLM tools for automation and accelerating analysis

Japanese language skills (welcome but not required)

Work Style

Hybrid work model centered around the Long Island (Deer Park) office

Regular on-site collaboration required with warehouse and operations teams

Flexible, performance-oriented work culture

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