Data Scientist III, Forecasting

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ShipBob, Inc.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2014

🛍️ eCommerce

☁️ SaaS

💰 $200M Series E on 2021-06

eCommerce • Logistics • SaaS

ShipBob, Inc. is a comprehensive 3PL (third-party logistics) service provider specializing in e-commerce order fulfillment. They offer a full stack fulfillment platform with OMS, IMS, RMS, ERP, and analytics to automate and streamline fulfillment processes. With a focus on omnichannel and B2B capabilities, ShipBob assists businesses in selling across online and in-person channels while offering services like inventory management, customization for unique unboxing experiences, and end-to-end managed freight. Their global network enables efficient 2-day shipping across the continental US and facilitates global expansion with fulfillment centers in multiple countries. Additionally, ShipBob integrates with popular eCommerce platforms like Shopify and Amazon, supporting a wide range of industries including health, beauty, and apparel. Their technology-driven approach enhances supply chain automation, providing reliable and transparent logistics solutions worldwide.

📋 Description

• Develop and deploy advanced forecasting models for sales, inventory, transportation, and transit time estimation to improve accuracy and operational efficiency. • Collaborate closely with fulfillment, transportation, revenue, product, engineering, and data science teams to translate business needs into predictive solutions that drive cost savings and enhance customer experience. • Own machine learning projects end-to-end—from ideation, data exploration, and prototyping to production deployment, monitoring, and continuous improvement. • Identify opportunities for optimization by leveraging predictive analytics to reduce costs, improve inventory placement, and minimize transit times across ShipBob’s global network. • Communicate insights and recommendations effectively through reports, dashboards, and presentations to senior stakeholders (Director to C-Suite), influencing strategic choices. • Promotes best practices in modeling and experimentation, ensuring scalability, reliability, and measurable impact. • Additional duties and responsibilities as necessary.

🎯 Requirements

• 4+ years of industry experience in data science, machine learning engineering, or technical leadership roles. • Proven ability to design, prototype, scale, and launch data science solutions that address real business needs. • Strong understanding of the machine learning lifecycle, including best practices, algorithms, and domains such as anomaly detection, NLP, computer vision, personalization, recommendation, and optimization. • Experience collaborating with cross-functional stakeholders and leveraging domain expertise to deliver impactful solutions. • Excellent programming skills in Python and familiarity with software engineering principles (testing, code reviews, deployment). • Working knowledge of data engineering fundamentals, including building data pipelines, processing, and storage. • Product-oriented mindset with the ability to apply conceptual and innovative thinking to create user-focused solutions. • Clear and effective communication skills for audiences at varying technical levels. • Graduate degree (MS/PhD) in a quantitative field (engineering, computer science, machine learning, operations research, statistics, mathematics) is a plus. • Experience with applied machine learning and cloud deployment (preferably in the Azure ecosystem) is highly desirable.

🏖️ Benefits

• Medical, Term & Accidental Insurance • All Purpose Leave (casual & sick time): 12 days • Earned Leave: 15 days • Public Holiday: 12 days • Generous Maternity & Paternity Leave • Quarterly Wellness Day • Work From Home Allowance • See Our High-Performing Culture >>>