Shippeo, the European leader in supply chain visibility, gives shippers, carriers, and end-customers instant access to predictive and real-time information of every delivery.

Shippeo’s machine-learning, proprietary algorithm dynamically calculates ETAs allowing shippers to quickly anticipate problems, proactively alert end-customers, and efficiently manage exceptions. Shippeo helps market-leading companies leverage transportation to deliver exceptional customer service and achieve operational excellence.

Founded in 2014, Shippeo tracks more than 7 million loads per year throughout Europe and connects to carriers in more than 62 countries. Shippeo's more than 160 employees have 22 different nationalities, and speak 20 languages!

What Shippeo does

Our product is composed of a mission critical SaaS web platform, with high traffic inbound/outbound integrations. Our mission is to anticipate problems and proactively alert end-customers so they can efficiently manage exceptions. We achieve this by collecting and matching millions of theoretical and real data from different stakeholders.

Shippeo gives visibility to shippers, carriers and customers by answering the following questions:

• where is the truck, and are there any foreseeable delays?

• what has actually been loaded and/or delivered, and are there any discrepancies?

• what are the levers for improvement for the transport operations?

The technical team is structured in three Tribes, each split into multiple feature teams:

1. Connect & Go Live: quickly connect shippers & carriers to have the project ‘live’

2. Track to React: make our product as sticky as possible for daily users

3. Analyze & Predict: leverage our data to build data products (extraction, analytics, decision support tools, algorithms)

What you will do

We are looking for a Senior Data Analyst to join our growing Analyze & Predict Tribe. The Analyze & Predict team is responsible for leveraging Shippeo’s data from our large customer and carrier base, to build data products that fall into 4 categories: 

• data extraction

• analytics (e.g., dashboards for internal use, dashboards embedded on the Shippeo platform)

• algorithms (e.g., predictive algorithms, anomaly detection algorithms)

• decision support tools

As a Senior Data Analyst, you will be joining the Analyze & Improve Feature Team (aka the BI/Analytics team) and focused on turning data into information, and information into insight. You will be responsible for building and maintaining new dashboards to be part of Shippeo’s Insights offer, building internal dashboards to standardize reporting processes for the Operations team, conducting in-depth analyses on prospects’ data to help the sales team build a solid business case, and measuring the value of implementing Shippeo post-sales.

Your missions will include: 

• Lead the delivery of analytics projects end to end

• Understand the requirements and define the business problem

• Fetch data from various data sources 

• Perform analyses through the use of statistical analysis, data mining, and data visualization techniques

• Build dashboards with the right data visualizations to communicate findings to various stakeholders

• Productize generic dashboards to expand Shippeo’s Insights offering

• Oversee the delivery and quality of regular reports and released dashboards

• Optimize the dashboards performance to improve user experience

• You have a degree (MSc or equivalent) in Mathematics, Computer Science or Statistics 

• 5+ years of experience as a data analyst

• Strong reporting skills using Tableau Software

• Strong knowledge and experience with relational databases (SQL, data modelling)

• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy

• Adept at report writing and presenting findings

• Data mining skills

• Programming skills in Python and experience with scientific programming libraries (Pandas, Numpy, Scipy) are a strong advantage

Recruitment Process : 

1. Preliminary call with our Recruiter

2. On-site round of interviews with the data team & case study

3. Interview with 1 or 2 founders