No more applications are being accepted for this job
Machine Learning Lead - Mumbai, India - Collinson
Description
CollinsonCollinsonis 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