Data Scientist, Sparkbox

Salary not provided

Python

Pandas

Scikit-Learn

Junior and Mid level

London

Remote from UK

More information about location

ML-powered merchandising tools

Job no longer available

ML-powered merchandising tools

1-20 employees

RetailB2BArtificial IntelligenceEnterpriseInternal toolsLogisticsBig dataAnalyticsMachine LearningeCommerce

Job no longer available

Salary not provided

Python

Pandas

Scikit-Learn

Junior and Mid level

London

Remote from UK

More information about location

1-20 employees

RetailB2BArtificial IntelligenceEnterpriseInternal toolsLogisticsBig dataAnalyticsMachine LearningeCommerce

Company mission

Sparkbox's mission is to modernise merchandising, eliminate guesswork, and empower humans with the tools they need to make data-driven retail decisions.

Job

Company

Role

Who you are

Experience of validating and improving the performance of prediction and optimisation algorithms
Experience of using machine learning, ideally prediction, in real world examples
Experience of statistical modelling, data mining, unstructured data analytics, natural language processing
Strong python programming skills and familiarity with tools such as scikit-learn, pandas, etc
Knowledgeable in a broad range of mathematical techniques, tools, and modelling frameworks and able to assess their relative merits and applicability to specific problems
Good communication skills: Ability to explain machine learning models and outcomes to team members outside the data science team
Flexibility & adaptability to changing priorities
Experience of using GCP Cloud (Compute, Big Query, Storage)
Comfortable processing large data sets for model estimation, insights and analysis with a working knowledge of SQL

What the job involves

Reporting to our Data and ML lead co-founder, you will be responsible for planning and delivering projects to build on and enhance the predictive modelling that sits behind our existing solutions
You’ll play a vital role in validating and improving the performance of deployed solutions, as well as developing the predictive analytics for new solutions that form part of our product road map
We are looking for someone who is a self-starter, motivated by the challenges of growing an early-stage technology company, with flexibility and adaptability to change priorities. On our Data Science team, you will play a critical role in developing new and existing machine learning models
This role would suit a candidate with machine learning experience, and an interest in technological developments and research relevant to machine learning in a retail and consumer goods environment

Application process

Apply via Welcome to the Jungle
Virtual interview with Kevin, our co-founder and ML/Data lead
In person interview with Kevin and our other co-founders, Lindsay and Matt. This will likely take place in London, and we may also ask you to bring along an example of your previous work

Salary benchmarks

Our take

Many retailers are still depending on antiquated manual processes to make inventory decisions. With the events of recent years, however, it’s become clear that failing to use accurate, data-driven insights to ensure good merchandise stock can take a heavy toll on business. Sparkbox is an AI-first startup hoping to change that. It helps brands optimise pricing, forecast demand, act on rebuying opportunities, and ensure their inventory is available across broader wholesale and 3rd party channels.

Profitability isn't the only benefit Sparkbox can sell itelf on, though. Data-driven fashion merchandising will help businesses get ahead of increasing levels of social and regulatory scrutiny regarding waste. The fashion industry is reported to generate around one tenth of all global carbon emissions, and in the UK alone around £140M worth of clothing ends up in landfill every year. So Sparkbox’s service is good for profit, but also increasingly good for business in a consumer market ever-more preoccupied with ethical values.

Kirsty

Company Specialist at Welcome to the Jungle

Company

Funding (1 round)

Mar 2022

$2.1m

SEED

Total funding: $2.1m

Company benefits

33 days holiday (25 days annual leave + UK bank holidays)
Stock options - We offer team members part ownership of our company as we believe you should be rewarded for being part of our growth
Flexible working - We are open to discussing part time or flexible working opportunities
Occasional travel - To conferences, trade shows, or trips to work with colleagues in our London/Manchester hubs
Extensive Development Opportunities: We encourage our team members to contribute based on their interests, and we’ll provide opportunities to work cross functionally across the business. Tell us what you need, and we’ll make it happen: we are committed to promoting great talent as our business and our needs grow
Health cash plan
Monthly team meetups with team lunch or drinks
Biannual team parties

Company HQ

Castlefield, Manchester, UK

Leadership

Matt Wong

(Co-founder)

Former project analyst with Balfour Beatty, ex retail consultant, and Forbes 30 under 30 recipient. Leads on Software development.

Lindsay Fisher

(Co-founder)

Former fashion merchandiser, ex merchandising consultant, and Forbes 30 under 30 recipient. Leads on business development and customer success.

Kevin Blackmore

(Co-founder)

25+ years of retail analytics experience, incl. as a Partner at Accenture and Vice-President of Insights at Best Buy. Leads on machine learning and data science.

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