Sr. Analyst, Supply Chain Planning

Blue Nile•New York, NY

3h•$75,000 - $90,000

About The Position

The Analyst, Supply Chain Planning is responsible for providing the analytical foundation on which our demand, supply, and inventory decisions are made, and for driving the improvement initiatives that advance our planning capability over time. This role sits within the Planning team alongside our demand and supply planners: where they own the execution of the forecast and the replenishment plan, you own the analysis, diagnostics, and reporting that make those decisions sharper, faster, and more defensible. You will build and automate the recurring performance reporting the team runs on, investigate and explain variance rather than simply surface it, and translate large, complex datasets into recommendations leadership can act on. This position offers broad exposure across forecasting, replenishment, and inventory strategy, and a direct path to grow into a planning or analytics leadership role as our team’s scope expands. One of the first tactical initiatives for this role will be building out our store sales performance and replenishment analytics. As our retail showroom footprint grows alongside e-commerce, we need clear visibility into how each location sells, where availability is constraining sales, and how inventory should be allocated and replenished across the network. You will own the analysis that establishes that visibility and turns it into a repeatable replenishment approach. We are a hands-on, code-forward planning organization. Our forecasting, replenishment, and reporting run on a Python-native analytics stack rather than on manual spreadsheets, and every member of the team is expected to work fluently in SQL, Python, and BI tooling. This is how we operate, and it is central to how this role creates value.

Requirements

3+ years in supply chain planning, demand planning, inventory analytics, business analysis, or a comparable analytical role
Demonstrated experience working with large, imperfect datasets and producing analysis that withstands scrutiny
Exposure to forecasting, replenishment, or inventory management concepts strongly preferred
Experience with retail store replenishment, allocation, or store performance analytics strongly valued
Experience in e-commerce, direct-to-consumer, retail, luxury goods, or premium consumer brands valued
Track record of identifying and delivering process or reporting improvements beneficial
Bachelor’s degree in Supply Chain, Business, Economics, Statistics, Analytics, Industrial Engineering, Data Science, or related field
Analytical rigor with genuine attention to detail: you reconcile before you report
Intellectual curiosity to pursue root cause rather than stopping at the first plausible explanation
Communication clarity translating technical analysis into actionable business recommendations
Business acumen connecting operational metrics to commercial and financial outcomes
Ownership mindset taking initiative to improve processes without waiting to be asked
Process orientation with a continuous improvement mindset
Comfort with ambiguity and the ability to prioritize across competing demands in a fast-paced environment
Collaborative approach working effectively across planning, commercial, and technology teams

Nice To Haves

Master’s degree in a quantitative discipline valued
APICS CPIM or CSCP certification beneficial
Certification or formal coursework in data analytics, statistics, or machine learning valued

Responsibilities

Build, automate, and maintain the recurring reporting and dashboards the Planning team operates on, including forecast accuracy and bias, service level and fill rate, inventory turns, weeks of supply, replenishment health, and fulfilment mix
Extract, clean, and reconcile data across multiple source systems into trustworthy, decision-ready views, applying disciplined validation before any number is published
Define and track planning KPIs against target, developing exception reporting that surfaces risk early rather than after the fact
Investigate variance to root cause and explain the drivers behind it, distinguishing genuine demand signal from data quality, seasonality, and one-off effects
Prepare the analytical inputs and supporting materials for the weekly planning cycle and the monthly IBP cadence
Partner day to day with the demand and supply planners, providing the data, backtests, and diagnostics required to make better forecasting and replenishment decisions
Support forecast review by quantifying forecast value add, benchmarking model output against naive baselines, and identifying where statistical output requires human override
Analyse demand patterns across categories and channels, including seasonality, promotional lift, new product introduction, and clearance behaviour
Model the service level and working capital implications of proposed planning decisions to support tradeoff discussions.
Build the reporting and analysis that establishes clear visibility into store level sales performance, including sell-through, productivity by location, category mix, and performance against plan
Analyse store inventory position and availability, quantifying lost sales opportunity where stock outs or thin coverage are constraining sell-through
Develop and refine store replenishment logic, including model stock, reorder triggers, and allocation rules across locations
Support allocation decisions for new product introduction, seasonal ranges, and high-demand SKUs across the store network
Compare demand signal and inventory productivity across store and e-commerce channels to inform how inventory is positioned across the network
Establish the recurring store performance and replenishment reporting cadence, and evolve it from initial build into standard operating process.
Support inventory strategy analysis across finished jewelry and, as the team’s scope expands, component and factory inventory: what to carry, how much, and where
Analyse inventory health including aging, coverage, excess and obsolescence risk, and availability gaps, and recommend corrective action
Contribute to assortment and SKU rationalisation analysis, quantifying the sales and working capital impact of range changes
Assess fulfilment method performance across our asset, vendor-stocked, and just-in-time models, and identify opportunities to improve availability and speed.
Identify friction and manual effort in current planning processes and propose data-backed improvements
Scope and drive supply chain planning improvement initiatives over time, from streamlining reporting through to enhancing forecasting and replenishment methodology and tooling
Automate recurring analysis and reporting in Python to reduce manual planning effort and free team capacity for judgement-based work
Document and standardise planning processes, definitions, and calculations so the team scales cleanly as its remit grows
Translate complex analysis into clear, concise recommendations for both technical and non-technical audiences
Partner cross-functionally with Merchandising, Finance, Operations, and Technology to align on data definitions and business context
Present findings and recommendations to senior stakeholders with clarity and appropriate confidence in the underlying data