Overview

We 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 Profile

The 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.Responsibilities

Analytics / Machine modellingAdvanced programming skills in SQL, SAS (desired), Python, and the ability to write production-level codeAdvise product stakeholders on feature and modelling accuracy and potential iterations which may drive improved model reliabilityExperience with deployment to production, using standard tools including GitHub, Jenkins, Sagemaker, Docker etcFamiliarity 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 preferredDevelop a testing framework and test model qualityFoster new and innovative machine-learning techniques and approachesGeneral

Passionate for continuous learning, experimenting, and applying open-source technologies within the machine modelling spaceWork closely with several data engineering and software engineering scrum teams to incorporate both new and enhancements to models to customer-facing applicationsEager to assure quality by a helping in developing strong validation and verification checks in the data engineering and modelling solutionsProvides strong technical expertise in adopting and contributing to open-source technologies related to Big Data and analyticsDrive significant technology initiatives end-to-end and across multiple layers of data and analytics engineeringWhat we are looking for

EssentialA Bachelor''s degree in Computer Science, Mathematics, Statistics, or a related quantitative field.At least 12 months experience SQL and Python for data extraction, analysis, and modellingUnderstanding of machine learning algorithms, predictive modelling, and data miningExcellent communication skills, with the ability to explain complex concepts to a non-technical audienceHighly analytical and detail-oriented with a passion for digging into data and problem-solvingProficiency in developing code with Python and SQLDesirableExperience in developing analytical models using the SAS platform, and/or experience writing models in SASMasters degree in Computer Science, Mathematics, Statistics, or a related quantitative field.Proficiency with SAS BaseExperience with AWS or similar cloud-based environmentsPrior experience in the Maritime industry, specific knowledge of AIS (Automatic Identification System) messagesOur Promise to You - Benefits

25 Days Holiday rising to 27 after 2 years'' serviceDay off for your birthday - because you deserve to celebrateLife Assurance for 4 x SalaryCompany 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 aboutAdditional leave for life events such as getting married or moving houseHealthy Lifestyle Subsidy up to £250 annuallyEnhanced Family Leave including maternity, paternity, and shared parental leaveWork from anywhere policy (up to 4 weeks per year, subject to approval) - giving you the flexibility to blend work and life on your termsCycle to Work schemeFlexible 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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