Machine Learning Lead

CollinsonCollinson

is a global loyalty and benefits company.We

use our expertise and products to craft customer experiences which enable

some of the world’s best-known brands to acquire, engage and retain the most

demanding and choice-rich customers. In particular, our unique expertise and

insight into high earning, frequent travellers allows us to create products

and solutions for our clients that inspire greater customer engagement to

drive more profitable relationships, enrich their travel experiences, protect

what matters and assist in in times of need.While

specialising in Financial Services, Travel and Retail, we also support

clients in multiple sectors. We have worked with over 90 airlines, 20 hotel

groups and more than 600 financial institutions and banks, with clients

including Accor Hotels, Air France KLM, American Express, British Airways,

Cathay Pacific, Diners Club, Mandarin Oriental, Mastercard, Radisson Hotel

Group, Sephora, Visa and VHI.We

take our 30 years’ experience working with these kinds of household names in

over 170 countries and help our clients to deliver the smarter experiences it

takes to differentiate their propositions and help them win deeper devotion

with their customers.Collinson

is a privately-owned entrepreneurial business with 2,000 passionate people

working in 20 locations worldwide.

Our solutions include Priority Pass,

the world’s best known airport experiences programme, while we are also the

trusted partner behind many of the leading financial services, airline and

hotel brand’s reward programmes and loyalty initiatives.Purpose

of the jobAs the Lead ML Engineer, you will serve as the

primary point of leadership for the ML platform team, guiding all aspects of

the design, development, and delivery of innovative data science and machine

learning products. Your responsibilities will encompass the full spectrum of

data product creation, from defining project objectives and acquiring data,

to exploring and pre-processing data, creating features, experimenting with

algorithms, deploying models, and continuously refining solutions through

iteration. You will also be tasked with building and maintaining the tools

and processes required to support this work.Also, you will play a critical role in driving

the development of machine learning pipelines for data-driven products and

services. Your responsibilities will include collecting data from various

business units and leveraging a centralized data platform to productionize

analytics and machine learning workflows. Additionally, you will be expected

to provide analytical expertise across the Collinson group, ensuring the

implementation of cloud-based solutions that meet the needs of both internal

and external clients from across Collinson's global footprint.As an innovator, you will be tasked with bringing

fresh ideas to the team and continuously exploring new and modern engineering

frameworks to enhance the overall offerings of the Collinson group. A key

aspect of this role will also be to collaborate with the data platform team

to integrate with the ML platform, and to support the growth and development

of the team's ML skillset.This role requires a deep technical expertise in

machine learning and data engineering, as well as excellent leadership and

collaboration skills. You must be able to communicate complex technical

concepts to both technical and non-technical audiences and have a proven

track record of delivering data products that meet business requirements.Key

ResponsibilitiesDesign,

Develop and DeliverMentor and manage a team of Machine Learning

Engineers, providing guidance, support, and feedback to help them grow and

develop professionally.Build a centralized ML platform to

productionize machine learning workflows, providing ML expertise across

Collinson's global footprint.Collaborate with the data platform team to

integrate with the ML platform and support the growth and development of the

team's ML skillset.Drive the development of machine learning

pipelines for data-driven products and servicesContribute to architecture and technical

decisions to create machine learning workflows and pipelines in cloud

(e.g.AWS)Collaborate with data scientists and

engineers to deploy new machine learning and deep learning models into

complex and mission critical production systemsSelect the right tool(s)/services(s) for the

job and make it work in productionPromote a culture of self-serve data

analytics by minimizing technical barriers to data access and understanding.Continuously explore and evaluate new and

innovative engineering frameworks and techniques to bring fresh ideas to the

team and enhance the overall offerings of the Collinson group.Collaborate with the data platform team to

integrate with the ML platform and support the growth and development of the

team's ML skillset.Identify and resolve technical issues in a

timely and effective manner, ensuring the quality and quantity of work

produced by the team is maximized.Communicate effectively with stakeholders,

both internal and external, to ensure that the team's work aligns with

business goals and expectations, and to provide regular updates on project

progress.Stay current with the latest research and

technology and communicate your knowledge throughout the enterpriseDay

to Day Activities will includeWorking on all stages of projects

(planning, development, quality control, production)Design, build and ongoing

maintenance of our strategic platform and tooling.Producing machine learning

models including supervised and unsupervised methodsRapidly prototyping

proof-of-concept ideaConverting proof-of-concept

projects to enterprise solutionsProducing reports and

presentations to communicate findings to stakeholdersInvestigate and understand emerging trends in

data-related approaches, performing horizon-scanning that present current and

future opportunities for the business.Knowledge,

skills and experience requiredIn-depth knowledge of data

science techniques, including data preparation, exploration, and

visualization.Expertise in data mining

techniques, including statistical modeling methods, time series, text mining,

optimization, and information retrieval.Ability to develop and implement

workflows using various techniques such as classification, clustering,

regression, and dimensionality reduction.Ability to design and apply

statistical analysis and modeling algorithms to solve complex problems in new

domains.Experience with industry best

practices in deploying data science/ML solutions.Strong understanding of the AWS

Well Architected Framework.Core Competencies:Proficiency in data science and

engineering technologies such as PySpark, PySpark ML, Python, Hive, Postgres,

and Sk-learn.Strong background in machine

learning, including collaborative filtering, NLP, TF-IDF, decision trees,

regression, and clustering.Data science and analytical

expertise.Excellent communication skills,

with the ability to interact effectively with both technical and

non-technical stakeholders.Proficiency in machine learning

and exploratory data analysis.Desired

Technical SkillsExperience in using Kubernetes

or similar orchestration systems.In-depth knowledge of relational

database systems such as Oracle, MySQL, and MS SQLServer.Exposure to messaging systems

such as Kafka.Knowledge of distributed

computing frameworks like Hadoop and Spark is a plus.Expertise in deep learning and

artificial intelligence, including MLP, CNN, DCNN, RNN, R-CNN, and GANS.Familiarity with cloud

providers, with a focus on AWS and Azure.Proficiency in visualization and

UI technologies, such as Tableau, Plotly, Python Flask, and Zeppelin.ExperienceHands-on experience in building

and deploying APIs.Strong experience with cloud

providers, specifically AWS and Azure, in both development and production

environments.Working knowledge of the Big

Data Ecosystem, including Hadoop.Proven ability to maintain

production-grade workflows.Experience with the full

software development lifecycle, including both Agile and Waterfall project

delivery methods.Consultative experience in data

science, engineering, or machine learning.Person

Specification:Self-motivator with a desire to learn new skills

and embrace new technologies in a constantly changing technology landscapeAbility to thrive in a fast-moving environmentAbility to show initiative, innovation and work

independently when requiredAbility to work at pace and tackle project

challenges in a collegiate, collaborative wayGoal and outcome orientatedThoroughness and attention to detailGood communication skills (ability to present,

inform and guide others)Ability to bridge communications between technical

and business focussed groupsComfortable working with people at all levels in

an organisationWillingness to take on a variety of roles and

responsibilities

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