Data Analyst — Consumer & Category Insights

Fenix ML

Remote · £28K – £36K (pro-rated, 2–3 days/week) · Part-time · Posted 5 months ago

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About the role

We make condiments. We\'ve been making condiments since 1991. Our smoked chilli sauce is stocked in Waitrose. Our mango habanero won a Great Taste Award two years running. We also make a very popular kimchi that we are quite proud of. None of this is particularly relevant to the job, but we thought you should know who you\'d be working for before reading further. We are a small company — 34 full-time employees, three production sites, and distribution through about 2,800 retail outlets in the UK and Ireland. Over the last two years we\'ve invested in proper data infrastructure for the first time: we have a Shopify-connected data warehouse, Nielsen category data, and retailer EPOS feeds from our three largest accounts. We now have more data than anyone in the company knows how to use, which is why we\'re hiring. This is a part-time role — we need someone two to three days a week. The work involves turning the data we have into analysis that our commercial director, our buyers, and our marketing manager can actually act on. If you have done analytics work in food, beverage, retail, or FMCG, that background will make you useful faster. But it is not a requirement. What we need is someone good with data who is also willing to explain what a p-value means to someone who last studied maths in 2004.

Responsibilities

Build a monthly category performance dashboard tracking our SKU performance against category benchmarks in our key retail accounts
Analyse customer purchase behaviour on our DTC Shopify channel to identify repeat purchase patterns and churn signals
Support our commercial director with retailer range review presentations — the data slide is usually the weakest one and we would like that to change
Build a baseline demand signal from EPOS data that our production planning team can use for rough-cut capacity planning
Document your analyses clearly enough that someone else could reproduce them when you are not available

Requirements

2+ years of data analysis in a commercial or operational environment
Python for data manipulation and analysis — Pandas at a working level is sufficient, you don\'t need to be building production systems
SQL for querying our data warehouse — you should be comfortable writing joins and aggregations without looking up syntax
Tableau for building dashboards and category analysis views that non-technical colleagues can use independently
Statistics at a practical level: trend analysis, correlation, and the honesty to communicate uncertainty rather than false precision
Familiarity with retail or FMCG data — EPOS, category management concepts, or Nielsen/Kantar — is a genuine advantage but not a hard requirement

Benefits

£28,000 – £36,000 pro-rated to 2–3 days per week
Fully remote — no office visits required unless you want a factory tour, which is a genuinely good day out
Flexible hours within the working week
An unreasonable quantity of free condiments — this is not a joke
A small team where your work will be visible and valued from the first month