Data Science Data Science Senior Data Scientist

4 weeks ago

London, United Kingdom Element Materials Technology Full time

Imagine having the opportunity to contribute to the build of high-impact digital products with a world-class tech team, all while working towards a greater purpose of making the world a better and safer place. Element, a well-established organization that touches billions of lives, is searching for a Data Scientist in London (hybrid) to help build a startup within their organization.
You will design and train performant models from scratch and create a powerful analytics engine fueled by cutting-edge technology and generative AI. You will be responsible for building, validating, and deploying machine learning models that drive our product's analytics engine. Operating in an Agile setting, you will be part of a cross functional team, collaborating closely with other Data Scientists, Data Engineers, Software Engineers, Product Owners and UX /UI Designers, to innovate and drive our product to new heights.

Build and deploy advanced machine learning models & design robust analytics engines for high-end digital products
Create repeatable, interpretable, dynamic and scalable models that are seamlessly incorporated into analytic data products
Collaborate with other data scientists to ideate and solve complex issues pertinent to data ingestion /curation, modality integration, model performance, model generalization
Stay up-to-date with latest industry trends and advances in data science, machine learning and generative AI
Advocate and educate on the value of data driven decision making focusing on the “how and why” of solving problems
Lead analytic approaches, integrating work into applications and tools with data engineers, business leads, analysts and developers
Engineer features by using your business acumen to find new ways to combine disparate internal and external data sources
Share your passion for Data Science with broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards
Collaborate, coach, and learn with a growing team of experienced Data Scientists

Bachelor’s in Data Science, Computer Science, Engineering, Statistics and 5+ years experience required OR MS or PhD in quantitative discipline and demonstrated Data Science skill set, plus 2+ years work experience
Extensive knowledge and expertise in building, testing, and deploying complex machine learning models that demonstrate high accuracy and robustness
Strong proficiency in Python, PostgreSQL and Azure Cloud Stack
Experience with tuning, deployment, monitoring and maintenance of models in production desired
Expertise in using and implementing cutting-edge machine learning algorithms, frameworks, and libraries, such as PyTorch, Keras, Tensorflow to solve clustering, classification, regression, and optimization problems on large scale data sets
Experience with Big Data technologies a plus —PySpark, H20.Must have proven ability to merge and transform disparate internal & external data sets together to create new features

When failure in use is not an option, we help customers make certain that their products, materials, processes and services are safe, compliant and fit for purpose. From early R&D, through complex regulatory approvals and into production, our global laboratory network of scientists, engineers, and technologists support customers to achieve assurance over product quality, sustainable outcomes, and market access.

We empower you to take charge of your career, and reward excellence and integrity with growth and development.

Industries across the world depend on our care, attention to detail and the absolute accuracy of our work. Diversity Statement

We are an equal opportunity employer that recognizes diversity and inclusion as fundamental to our Vision of becoming “the world’s most trusted testing partner”.

All suitably qualified candidates will receive consideration for employment on the basis of objective work related criteria and without regard for the following: age, disability, ethnic origin, gender, marital status, race, religion, responsibility of dependents, sexual orientation, or gender identity or other characteristics in accordance with the applicable governing laws or other characteristics in accordance with the applicable governing laws.

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