Headquartered in North York, ON, with employees in Canada, the US, China and India, NewAge is an industry- leading manufacturer and distributor of premium home improvement solutions.
Our products are sold through major online retailers such as Lowes, The Home Depot, Costco, Amazon, and Wayfair as well as our own e-commerce site. But what makes us unique is that we provide a truly cohesive customer experience, from free expert assistance designing and planning new spaces to delivery and professional installation.
Our collaborative, inclusive team atmosphere nurtures personal growth, career advancement and job satisfaction, as evidenced by our certification as a Great Place to Work in Canada.
With tremendous pride, we continue to receive a growing number of industry accolades including over 75 unique product patents, awards for our team of expert designers, prominent ranking on the Profit 500 list of Canada’s fastest growing companies, and the naming of our founders to the Top 40 under 40 in Canada by BNN Bloomberg.
We are also proud to be the official jersey emblem partner of the New Orleans Pelicans and have forged strategic partnerships with USA Hockey and Habitat for Humanity. These partnerships reflect our passion for teamwork, excellence, and community involvement.
As our journey to becoming the preferred choice for premium home improvement solutions continues, we’re adding ambitious, driven, passionate members to our team who are inspired to be their best and ready to make a difference.
The Sr. Manager, Order Fulfillment & Data Analytics owns the end-to-end order lifecycle — from the moment an order arrives to the moment it reaches the consumer's door. The role exists to move four numbers: more orders released without human intervention, more orders shipped the ideal way, less cost to fulfill each one, and less time between order and delivery.
KEY RESPONSIBILITIES:
Build the Automation Engine — OMS & TMS Insourcing
- Lead the business case, vendor evaluation, selection, and implementation of an in-house or third party OMS and TMS platform; own the ROI model, BRD, technical specifications, and PMO delivery plan.
- Migrate all order-import, validation, allocation, and routing logic from external or manual handling into the owned platform, with version control, audit trail, and documented decision rules.
- Partner with IT and external development resources on architecture, API/EDI integration, ERP interoperability, and data model design; act as business owner and final arbiter of order logic.
- Build a centralized datastore consolidating order, inventory, freight, carrier, retailer, and financial data as the single system of record; treat master data quality as a prerequisite, since automation performs only as well as the data behind it.
Automate the Order Decision
- Baseline touchless performance and build a taxonomy of manual-touch reasons, quantified by volume, labour cost, and cycle-time impact.
- Design, deploy, and continually tune the rule sets, tolerances, and exception logic that release orders without human intervention — and sustain that performance as volume, channel mix, and retailer requirements change.
- Apply AI/ML to order screening: anomaly and fraud detection, address and data-quality auto-correction, predictive hold scoring, and auto-resolution of recurring exception types.
- Deploy AI-assisted triage for orders that still require review, feeding every resolution back into the rules engine; treat each recurring manual touch as a defect with a named owner and closure date.
Raise the Ideal Shipment Rate
- Define and operationalize the “ideal shipment” standard — complete, single shipment, correct node, correct cartonization, correct service level, no rework — as a measured, reportable rate.
- Attack the drivers of non-ideal shipments: splits, short ships, wrong-node allocation, oversized cartons, avoidable expedites, re-ships, and returns caused by fulfillment error.
- Optimize inventory positioning and allocation logic so orders fill complete from the node closest to the consumer; partner with Demand Planning and Inventory on placement, not just execution.
- Deploy AI-driven cartonization and packing optimization to cut dimensional weight, transit damage, and material spend; automate pre-shipment validation against retailer routing guides, ASN, and labelling requirements.
Lower the Cost of Fulfillment
- Own cost-to-serve visibility at the order, SKU, channel, retailer, carrier, and lane level; make margin leakage visible and attributable.
- Implement AI-assisted rate shopping and carrier selection that optimizes landed cost against the service commitment, rather than defaulting to incumbents or static routing tables.
- Reduce the cost of failure — re-ships, expedites, chargebacks, damage claims, returns processing — by eliminating the upstream errors that generate them; build predictive modelling that flags orders and programs trending below target margin before they ship.
- Prepare and manage department labour and SG&A budgets; negotiate and manage 3PL, carrier, and technology agreements and hold partners to contracted rates and service levels with data.
Shorten Time to the Consumer
- Own order cycle time end to end — receipt to release, release to pickup, pickup to doorstep — and drive down each segment independently.
- Eliminate the internal delays that consume transit days: slow order release, hold queues, wave timing, inventory inaccuracy, and late carrier pickups.
- Deploy predictive delay detection that flags at-risk orders in flight and triggers automated intervention and proactive customer communication before the promised date is missed.
- Improve delivery-promise accuracy at the point of order; manage carrier and 3PL performance against transit commitments and reallocate volume based on measured lane-level results.
Analytics, Gap Identification & Cross-Functional Accountability
- Lead automated dashboards and self-serve reporting that give each function line-of-sight to the metrics it controls, with drill-down to the transaction level.
- Deliver recurring gap analysis quantifying where internal processes and external partners fail against standard, ranked by financial impact; convert findings into a prioritized action register with named owners and due dates.
- Chair a recurring cross-functional operating review; hold Logistics, Customer Service, Sales, IT, Finance, and external partners accountable to committed improvements and elevate stalled items.
- Use AI to accelerate the analysis itself — natural-language querying of the datastore, automated root-cause narratives, anomaly alerting, generated executive summaries — so the team spends its time on decisions, not report production.
Leadership & Team Development
- Hire, develop, and lead a team spanning order management operations and data analytics; build succession depth in both disciplines.
- Raise the automation and AI fluency of the department — tooling, standards, and safe-use guidelines so analysts and coordinators build and use automation daily.
- Maintain workflows, process documentation, technical specifications, and SOPs; systematize department knowledge rather than leaving it resident in individuals.
- Set individual objectives tied to department outcomes; coach to performance and hold the team to the same accountability standard applied cross-functionally. Other related tasks as assigned.
QUALIFICATIONS:
- Post-secondary degree in Business, Supply Chain, Statistics, Computer Science, or a related field.
- Minimum 10 years managing ecommerce and/or retail order management and fulfillment processes, in a highly analytical, metrics-driven environment; minimum 5 years leading and developing a team.
- Demonstrated experience implementing or insourcing an OMS and/or TMS platform — vendor selection, integration, and post-go-live optimization.
- Proven track record automating manual fulfillment processes with measurable improvement in cost per order, shipment quality, or delivery speed.
- Strong working knowledge of ERP systems, API and EDI transactions, WMS/3PL integration, and order management architecture.
- Advanced analytical capability — SQL and BI tooling (Power BI or equivalent) required; Python/R and data modelling strongly preferred; advanced Microsoft Office Suite skills mandatory.
- Hands-on experience applying AI/ML to operational problems — forecasting, classification, anomaly detection, optimization, or generative AI. Experience deploying AI into a live operational workflow is a significant asset.
- Experience managing 3PL, carrier, and technology vendor relationships, including contract negotiation and SLA enforcement.
TRAVEL REQUIREMENTS:
- Travel may be required based on current or future business needs within Canada and the US
NEWAGE OFFERS:
- Salary and bonus is based on experience and highly competitive for the right candidate. This is an existing vacancy and the base salary range for this position is $130,000 to $160,000 annually (CAD) at the time of the posting.
- Benefits Package
- An opportunity within a growing, fast-paced company, well established in its industry.
- Fun! We celebrate successes and hold special events to build strong teams.
- Our teams work under a remote-first Hybrid model, with the ease of having our North York office accessible for collaboration and/or quiet workspace.
We thank all interested candidates for applying and will contact those who qualify for an interview. No phone calls please. Offers of employment are contingent on the successful completion of a thorough background check.
NewAge Products is an equal opportunity employer, committed to inclusion and diversity. We provide employment accommodation in accordance with the Ontario Human Rights Code and the Accessibility for Ontarians with Disabilities Act. If contacted for an employment opportunity, please advise Human Resources if you require any accommodation.
AI enabled tools may be used to support parts of the recruitment process. All hiring decisions are made by human reviewers.