Website Imperial Dade
Imperial Dade
Company : Imperial Dade
Overview:
Imperial Dade, a leading national distributor, is seeking a highly motivated and skilled Senior Data Scientist to join our dynamic team in Jersey City, NJ. In this pivotal role, you will work alongside peer data scientists to develop, enhance, and maintain critical pricing models, leveraging advanced data engineering and machine learning techniques to drive high-impact business decisions. You'll also have the opportunity to work closely with and learn from our new, dynamic leader who is set to transform our revenue management strategy!
Salary: $135,000 – $165,000/yr.
Imperial Dade is the leading independently owned and operated distributor of foodservice packaging and janitorial supplies in North America. As a provider of customized supply chain solutions, we serve customers in many business-to-business market segments including restaurants, grocery stores, healthcare, sports and entertainment, and cruise lines. Founded in 1935 and headquartered in New Jersey, Imperial Dade serves as a mission-critical partner to more than 120,000 customers through our footprint of 130+ branches.
**All correspondence will come directly from Imperial Dade and not a personal email address.*
Responsibilities:
You will:
- Lead the design, development, and deployment of advanced machine learning models and statistical analyses to solve critical business challenges.
- Collaborate with cross-functional teams, including engineering, product, operations, and finance, to identify opportunities and deliver data-driven solutions.
- Provide technical mentorship to junior data scientists and analysts, guiding best practices and fostering a culture of innovation.
- Translate complex analytical findings into clear, actionable insights for technical and non-technical stakeholders.
- Design and manage experimentation strategies (e.g., A/B testing, causal inference) to drive data-backed decision-making.
- Ensure the integrity, quality, and governance of data throughout the modeling lifecycle.
- Support the scaling and automation of model deployment pipelines and monitoring systems.
Qualifications:
You will:
- Master’s or PhD (strongly preferred) in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
- 5+ years of experience in data science, advanced analytics, or machine learning with a deep understanding of statistical methods, machine learning algorithms, optimization, and predictive modeling.
- Strong proficiency in Python or R, and SQL
- Experience deploying models into production and monitoring performance.
- Excellent communication skills, with the ability to convey complex technical concepts to executive and non-technical audiences.
- Familiarity with cloud platforms (Azure, AWS, GCP) and MLOps tools.
- Experience working with big data frameworks (Spark, Hadoop, Databricks).
We offer a dynamic environment for our more than 7,500 employees to work, learn, and grow professionally. We value our people and strive to create rewarding career opportunities by offering competitive salaries and benefits (medical, dental, vision), a 401(k) program with company match, life insurance, a generous paid time off package, educational reimbursement, paid family leave, and adoption assistance. We are excited to invite talented individuals with a passion for excellence to join our team.
Imperial Dade is an EEO Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, pregnancy, status as a parent, national origin, age, disability (physical or mental), family medical history, or genetic information, political affiliation, military service, or other non-merit-based factors.
Our company is a Fair Chance employer, committed to providing opportunities for qualified individuals with past justice system involvement. We believe in assessing candidates based on their skills and experience. A conditional offer of employment will be contingent upon the successful completion of a background check, consistent with applicable federal, state, and local laws.