Full-Time

Senior Data Science Engineer

Confirmed live in the last 24 hours

dunnhumby

dunnhumby

1,001-5,000 employees

Customer data analytics for retail marketing

Data & Analytics
Consulting
Venture Capital
Consumer Goods

Senior

London, UK

Category
Data Science
Data & Analytics
Required Skills
Agile
Python
Airflow
Apache Spark
SQL
Machine Learning
Docker
Hadoop
Development Operations (DevOps)
Requirements
  • Strong experience building python packages, installable with pip/conda
  • Experience processing big data, ideally in a Hadoop/Spark environment
  • Experience working with relational databases, and SQL-like operations
  • Experience with Airflow / orchestration tooling is beneficial
  • Understanding of Continuous Integration/Continuous Delivery (CI/CD) & DevOps processes, and experience applying them within an Agile framework is beneficial
  • Experience with containerisation beneficial, including Docker/Podman
  • Experience building highly scalable applications with Spark highly beneficial
  • Understanding of machine learning techniques such as regularised regression, clustering or tree-based ensembles would be an added advantage
Responsibilities
  • Design, develop, and support standalone, reusable python packages that surface novel data science solutions, and are fundamental to best-in-class, global products
  • Build processes and tools to support the research of global science methods, including visual dashboards to showcase their approaches
  • Advocate for and support the development of fundamental engineering skills across the wider team and business
Desired Qualifications
  • Experience with Airflow / orchestration tooling is beneficial
  • Understanding of Continuous Integration/Continuous Delivery (CI/CD) & DevOps processes, and experience applying them within an Agile framework is beneficial
  • Experience with containerisation beneficial, including Docker/Podman
  • Experience building highly scalable applications with Spark highly beneficial
  • Understanding of machine learning techniques such as regularised regression, clustering or tree-based ensembles would be an added advantage

dunnhumby specializes in Customer Data Science, providing insights that help retailers and brands improve customer experiences. The company analyzes customer behavior and preferences using advanced data analytics, which allows clients to create targeted marketing campaigns. Unlike many competitors, dunnhumby does not store personal information but uses unique identifiers to gather data from various sources. Their business model includes offering services such as media solutions and personalized marketing strategies, which enhance customer interactions and optimize marketing efforts. Additionally, dunnhumby Ventures invests in early-stage retail technology startups, ensuring the company remains at the forefront of retail innovation. The main goal of dunnhumby is to empower businesses to engage customers more effectively and drive sales through data-driven strategies.

Company Stage

Acquired

Total Funding

N/A

Headquarters

London, United Kingdom

Founded

1989

Simplify Jobs

Simplify's Take

What believers are saying

  • Real-time data analytics partnerships enhance dunnhumby's market adaptability.
  • AI-powered tools position dunnhumby as a leader in competitive retail analysis.
  • The Retail Innovation Network fosters collaboration, boosting innovation in retail technology.

What critics are saying

  • Departure of key media team member may disrupt dunnhumby's media strategy.
  • Challenges in integrating startups with enterprises could misalign innovation goals.
  • Data privacy concerns may arise from partnerships, affecting client trust.

What makes dunnhumby unique

  • dunnhumby leverages AI to optimize product selection and inventory management.
  • The company offers a unique Competitive Threat Evaluator for strategic market insights.
  • dunnhumby partners with startups through its Retail Innovation Network to drive retail tech.

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Benefits

Flexible Work Hours

Unlimited Paid Time Off

Remote Work Options