Sr. Data Scientist

Description

DESCRIPTION*The Role can be based in the United Kingdom, Luxembourg, Germany, Ireland and France.Amazon Web Services (AWS) provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries worldwide. In a fast-paced, high-growth environment, making data-driven decisions is critical.The EMEA AWS Solutions Architecture (SA) organisation is looking for a strong, talented Senior Data Scientist to build models, discover insights and identify opportunities through the use of statistics, machine learning, and deep learning to drive business and operational improvements. We are looking for a thought leader, and you demonstrate this by delivering solutions, not just by having ideas. We encourage you to shape the business with data-driven recommendations. A successful candidate has an entrepreneurial spirit and wants to make a significant impact. You will develop strong working relationships and thrive in a collaborative team environment. Your role requires the ability to influence and interact with a broad range of stakeholders (technical and non-technical). You draw from a broad data science expertise to mentor Data Scientists and Business Intelligence Engineers, following a rigorous scientific methodology while providing leadership on complex analytical topics. You provide guidance on cutting-edge methods in big data processing, data science literature, experimentation and careful consideration of modelling decisions. We expect you to have data science breadth and depth in predictive modelling (supervised learning) and unsupervised learning (clustering).As a Senior Data Scientist on our team, you will have opportunities to develop and evaluate machine learning models using large data sets and cloud services to drive growth. Working closely with other technical colleagues, you will have joint responsibility for our team's data infrastructure. You will have the opportunity to apply various machine learning and predictive algorithms on some of the world's largest data sets and influence over the long-term evolution of our data science roadmap. You will need to be entrepreneurial, can deal with ambiguity and like to work in a highly collaborative environment. You will identify specific and actionable opportunities to solve existing business problems and collaborate with multiple stakeholder teams to deliver future innovation. You need to be a sophisticated user of advanced quantitative techniques and data visualisation and an expert at synthesising and communicating insights and recommendations to audiences of varying levels of technical sophistication.Your role is critical and highly visible across the organisation and plays a key role in developing insights. These insights are used to lead decision making around resource allocation, program effectiveness, productivity analysis and business impact. You will work closely with the EMEA Solution Architect leadership team and the Worldwide Operations team and drive operational efficiency of field activities. Your customers are individual Solution Architects, management, and AWS senior and executive leadership.Come build the future with us.Key Responsibilities· Develop predictive models and decision science to help measure and improve the impact of our Solution Architects (SA) on our customers (e.g. predicting and optimising the best actions to take, predicting the best sequence of SA activities, data cleansing at scale, resource allocation, etc.)· Drive data science best practices and mentoring junior team members based on your in-depth knowledge in theoretical and practical data science disciplines.· Proactively seek to identify business opportunities and provide solutions based on a broad and deep knowledge of Amazon's data resources, industry best practices, and work done by other teams.· Partner with, coordinate, and influence multiple teams outside the EMEA Solution Architecture (SA) Business Operations team (SA Managers, SA Leaders, Sales Operations, etc.), to support key initiatives.· Be the voice of the customer (end customer and data consumer), aligning stakeholders with scalable mechanisms to incorporate our models into product and engineering decision-making processes.· Drive and promote experimentation culture (e.g. A/B testing) with a data-driven mindset and measurable approach.BASIC QUALIFICATIONS· Master's degree with 5 years relevant experience in a highly quantitative field (Machine Learning, Data Science, Computer Science, Statistics, Mathematics, Operational Research, etc.).· Hands-on industry experience in predictive modelling and analysis, as an ML engineer or data scientist role, applying various ML techniques, and understanding the key parameters that affect their performance.· Experience with Python, R, or other statistical/machine learning software.· Proficient with using a scripting language such as Python and data manipulation/analysis libraries such as Scikit-learn and Pandas for analysing and modelling data.· Experienced in using multiple data science methodologies to solve complex business problems (e.g. statistical analysis, machine learning and deep learning techniques, data modelling, regression modelling, demand modelling, etc.).· Experience with productionizing Machine Learning Models.· Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Theano, Keras, PyTorch, Gluon and Caffe.· Experienced in handling terabyte-sized data sets, diving into data to discover hidden patterns, using data visualisation tools, using SQL and databases in a business environment.· Ability to distil informal customer requirements into problem definitions, dealing with ambiguity and competing objectives.· Proven ability to communicate verbally and in writing to technical peers and leadership teams with various technical knowledge levels; educate them about our systems, and share insights and data-driven recommendations.PREFERRED QUALIFICATIONS· A PhD degree in a highly quantitative field (Machine Learning, AI, Computer Science, Statistics, Mathematics, Operational Research, etc.).· 7+ years' experience in an ML or Data Scientist role with a large technology company.· Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval, etc.· Skilled with Python, Java, Scala, or other programming language, as well as SQL or similar scripting language.· Functional knowledge of AWS Services such as SageMaker, S3, Glue, Athena, Lambda, EC2, AWS Batch, Step Function or other cloud technologies.· Advanced knowledge and expertise with Data modelling skills, advanced SQL, MySQL, Redshift and Columnar Databases.· Demonstrated industry leadership in the fields of Database and/or Data Warehousing, Data Sciences and Big Data processing.· Experience mentoring junior team members.Amazon is committed to a diverse and inclusive workplace.
 
 
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