OverviewWe are the industry experts delivering actionable maritime insight, data, technology, and analytics trusted by 60,000 professionals across the globe to drive commercial advantage, evaluate risk, and support the efficient and lawful movement of seaborne trade.

Our data is collected only from the most reputable partners and accurate sources, many of which are exclusive to us and our customers. Our advanced analytics, artificial intelligence, and industry expertise transform our unparalleled data into powerful insight delivered through data and analytics platforms and services, news and commentary, and publications that help professionals in maritime operations, risk, and compliance stay well informed. Leading seaborne trade through change with data transparency, innovative technology, and human ingenuity.

Role ProfileThe Data Scientist will join our advanced analytics group to assist us in building various advanced statistical, deterministic and machine learning models to create behavioural profiling on a range of data features relating to the global shipping fleet.

This role expects customer-facing interaction: Analytical model explainability is a core principle in how we develop models, and our data scientists assist sales and product colleagues articulate to customers the quality of our analytical models.

The role will report to Head of Data Engineering and will be based in the company headquarters in London.

Key Responsibilities

Analytics / Machine modelling

Advanced programming skills in SQL, SAS (desired), Python, and the ability to write production-level code

Advise product stakeholders on feature and modelling accuracy and potential iterations which may drive improved model reliability

Experience with deployment to production, using standard tools including GitHub, Jenkins, Sagemaker, Docker etc

Familiarity with the most standard Python libraries used in ML (e.g., Scikit-Learn, Pandas, Numpy, LightGBM, XGBoost, just to name a few)

Experienced in evaluating, training, and communicating the performance of ML models (e.g., supervised models, such as gradient boosting, logistic regressions etc. and non-supervised approaches, including clustering)

Ability to evangelize next-generation infrastructure in analytics space (batch, near real-time, real-time technologies), using both SAS components and AWS tooling (e.g., Redshift, SQS, Kinesis)

Strong familiarity with spatial-temporal data sets, with exposure to maritime data preferred

Develop a testing framework and test model quality

Foster new and innovative machine-learning techniques and approaches

General

Passionate for continuous learning, experimenting, and applying open-source technologies within the machine modelling space

Work closely with several data engineering and software engineering scrum teams to incorporate both new and enhancements to models to customer-facing applications

Eager to assure quality by a helping in developing strong validation and verification checks in the data engineering and modelling solutions

Provides strong technical expertise in adopting and contributing to open-source technologies related to Big Data and analytics

Drive significant technology initiatives end-to-end and across multiple layers of data and analytics engineering

What we are looking forEssential

A Bachelors’ degree in Computer Science, Mathematics, Statistics, or a related quantitative field.

At least 12 months experience SQL and Python for data extraction, analysis, and modelling

Understanding of machine learning algorithms, predictive modelling, and data mining

Excellent communication skills, with the ability to explain complex concepts to a non-technical audience

Highly analytical and detail-oriented with a passion for digging into data and problem-solving

Proficiency in developing code with Python and SQL

Experience in developing analytical models using the SAS platform, and/or experience writing models in SAS

Master’s degree in Computer Science, Mathematics, Statistics, or a related quantitative field.

Proficiency with SAS Base

Experience with AWS or similar cloud-based environments

Prior experience in the Maritime industry, specific knowledge of AIS (Automatic Identification System) messages

Our Promise to You – Benefits

25 Days Holiday rising to 27 after 2 years’ service

Day off for your birthday - because you deserve to celebrate

Life Assurance for 4 x Salary

Company pension scheme: employee contribution of 5% basic salary, matched by an employer contribution of 5%

Up to 4 Days Paid Volunteering per year to support causes you care about

Additional leave for life events such as getting married or moving house

Healthy Lifestyle Subsidy up to £250 annually

Enhanced Family Leave including maternity, paternity, and shared parental leave

Work from anywhere policy (up to 4 weeks per year, subject to approval)

Cycle to Work scheme

Flexible benefits: Private Healthcare Plan, Dental Insurance, Medical Expenses Cash Plan, Health Screening, Critical Illness Cover, Employee Assistance Programme and option to purchase 3 additional days of annual leave

We know that sometimes the ''perfect candidate'' doesn''t exist, and that people can be put off applying for a job if they don''t fit all the requirements. If you''re excited about working for us and have most, but not all the skills or experience we''re looking for, please go ahead and apply. You could be just what we need!

We believe strongly in the value of diversity and creating supportive, inclusive environments where our colleagues can succeed. As such, we are proud to be an Equal Opportunity Employer. We do not discriminate based on race, colour, ancestry, national origin, religion, or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other protected characteristics under federal, state or local law.

Please let us know of any adjustments we need to make for you to show us your best self.

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