Machine Learning Expert
Location – UK
A global leader in consulting, technology services and digital transformation, Capgemini is at the forefront of innovation to address the entire breadth of clients' opportunities in the evolving world of cloud, digital and platforms. Building on its strong 50-year heritage and deep industry-specific expertise, Capgemini enables organizations to realize their business ambitions through an array of services from strategy to operations. Capgemini is driven by the conviction that the business value of technology comes from and through people. It is a multicultural company of 200,000 team members in over 40 countries. The Group reported 2018 global revenues of EUR 13.2 billion. People matter, results count.
Who you’ll be working with
As part of the Data Science Lab within Global IT, you will work in a collaborative environment with internal and product stakeholder resources.
The focus of your role
To understand end user experiences, improve experience and solutions, and present findings to client executives while solving real-world problems. If you are passionate about solving problems in the realm of cognitive computing, big data, machine learning and AI while utilizing business acumen, statistical understanding, and technical know-how, the Data Science Lab practice group at Capgemini is the best place to grow your career.
What you’ll do
- Work in collaborative environment with global teams to drive ML-driven productivity and optimal technology experiences across a series of key end user systems.
- Quickly understand end user system and stakeholder needs, develop measurement reports and new KPIs, improved solutions, and articulate findings to stakeholders and executives.
- Provide data-driven recommendations to clients by clearly articulating complex technical concepts through generation and delivery of presentations.
- Analyze and model both structured and unstructured data from several distributed client and publicly available sources.
- Deep data wrangling ability to integrate key static and streaming data sources, perform data cleansing and deriving new predictor and input variables from the resulting datasets to support analysis and ML efforts.
- Perform EDA and feature engineering to both inform the development of statistical models and generate improve model performance and flexibility.
- Design and build scalable machine learning models to meet the needs of given client engagement.
- Develop automation deployments to automate critical ML capabilities to monitor ongoing end user service usage and improvements
- Assist in growing data science lab initiative by meeting business goals through stakeholder discover interviews, contributing to the development of a data science lab environment, identifying, refining and setting up ongoing measurement within identified end user service platforms.
- Participate in client discussions, interact with both technical and business contacts throughout the organization to articulate the value of data science approaches, different service offerings and guide them on implementation of the same.
- Collaborate with product managers in a broad range of sectors to identify business use cases and develop solutions in driving impact through data science and analytics, communicate results, and inform practice group through reports and presentations.
What you’ll bring
- Skilled prior experience as a data scientist or on advanced analytics / statistics projects.
- Familiarity with data mining approaches such as CRISP-DM that will be used to guide the planning and resources for the program
- Master’s degree from top tier college/university in Computer Science, Statistics, Economics, Physics, Engineering, Mathematics, or other closely related field.
- PhD preferred.
- Strong understanding and application of statistical methods and skills: distributions, experimental design, variance analysis, A/B testing, and regression.
- Statistical emphasis on data mining techniques, Bayesian Networks Inference, CHAID, CART, association rule, linear and non-linear regression, hierarchical mixed models/multi-level modeling, and ability to answer questions about underlying algorithms and processes.
- Experience with both Bayesian and frequentist methodologies.
- Mastery of statistical software, scripting languages, and packages (e.g. R, Matlab, SAS, Python, Pearl, Scikit-learn, Caffe, SAP Predictive Analytics, KXEN, ect.).
- Knowledge of or experience working with database systems (e.g. SQL, NoSQL, MongoDB, Postgres, ect.)
- Experience working with big data distributed programming languages, and ecosystems (e.g. S3, EC2, Hadoop/MapReduce, Pig, Hive, Spark, SAP HANA, ect.)
- Expertise in machine learning algorithms and experience using the following ML techniques: Logistic Regression, Decision Trees, Random Forests, Gradient Boosting, SVMs, Time Series, KMeans, Clustering, NMF).
- Preferred experience with NLP, Graph Theory, Neural Networks (RNNs/CNNs), sentiment analysis, and Azure ML.
- Experience building scalable data pipelines and with data engineering/ feature engineering.
- Preferred experience with web-scrapping
What We’ll Offer You
Professional development. Accelerated career progression. An environment that encourages entrepreneurial spirit. It’s all on offer at Capgemini. And although collaboration is at the core of the way we work, we also recognise individual needs with a flexible benefits package you can tailor to suit you.
Why We’re Different
At Capgemini, we help organisations across the world become more agile, more competitive and more successful. Smart, tailored, often-groundbreaking technical solutions to complex problems are the norm. But so, too, is a culture that’s as collaborative as it is forward thinking. Working closely with each other, and with our clients, we get under the skin of businesses and to the heart of their goals. You will too.
Capgemini positively encourages applications from suitably qualified and eligible candidates regardless of sex, race, disability, age, sexual orientation, gender reassignment, religion or belief, marital status, or pregnancy and maternity. We are committed to hiring, developing and retaining the best people to deliver innovative, world-class solutions for our clients. We foster an inclusive culture that enables everyone to achieve their full potential and enjoy a fulfilling career with us. Our comprehensive flexible benefits package and lifestyle policies enable our employees to balance their individual, family and work-life needs.