Data Analytics Lead Deloitte Omnia - Job Type:
Calgary, Alberta, Canada
All Available Locations:
External Posting Description 13;
Omnia, Deloittes Artificial Intelligence practice is comprised of specialized experts with hands:on experience, and cutting:edge information assets that facilitate successful Artificial Intelligence (AI) transformations. We develop AI:enabled solutions to address all aspects of a clients transformative journey with disciplined focus on business outcomes.
Your role at Deloitte
As a Manager, you may be involved in any one of these activities:
:Take a leading role in designing, executing and delivering advisory services to high growth organizations with a diverse team consisting of data scientists, data architects, software developers, information designers, and business/industry subject matter experts
:Lead, guide, and perform hands on statistical modelling and mathematical modeling, and work with junior resources to lead solution design and ensure quality of models and analysis
:Play a leading role in the overall sales process, including creating and fostering client relationships, identifying new approaches and opportunities, and managing leads across the entire sales cycle
:Manage different components of projects including managing teams of analysts and senior analysts of various sizes, day:to:day execution of the analytical solution and overall project, and communication with internal stakeholders and external clients.
:Lead the development of the methodology for analytical solutions for clients business problems
:Lead teams to integrate, and aggregate large amounts of data on a granular level, from structured and unstructured data sources to prepare analytical data set.
:Participate in various structured and ad:hoc analysis projects with cross:functional teams within Deloitte
:Lead the planning, data collection, and data analysis on client projects, and lead pitches and management of proposal bids 13;
External Posting Qualifications 13;
:Strong experience with applied statistical analytical techniques, data mining, and predictive models. Experience in clustering / segmentation, graph analysis, natural language processing, and / or other machine learning techniques preferred
:Specifically, 5 to 8 years work experience in the field of data science. Practical experience in building and deploying predictive models within large organizations, as well as building and data science leading teams
:Applying supervised and unsupervised machine learning techniques to applied problems such as customer segmentation, fraud or risk analysis, revenue or product usage forecasting, etc.
:Experience in working with databases and Big Data platforms to collect, transform and extract the right information for a machine learning use case
:Experience in translating machine learning solutions to business value and driving deployment and adoption across organizations
:Minimum of Honors Bachelors degree in a quantitative discipline including Econometrics, Petroleum Engineering, Chemical Engineering, Decision Sciences, Applied Mathematics, Statistics, or other quantitative field is required. Advanced degree (MA/MSc, Ph.D. equivalent or higher) is preferred
:Statistical software experience using (one or more): Python, R, SAS, SPSS Modeller, H2O, Data science Workbench, Model Management, Angoss Knowledge Studio, RapidMiner, or similar tools is required
:Database and programming languages experience and data manipulation and integration skills using (one or more) SQL, Oracle, Hadoop, NoSQL Databases, or similar tools is required
:Project management and people management experience is required
:Professional services, consulting, or advisory experience is preferred
:Strong track record exemplifying ability to quickly understand business problems, developing solutions and insights, and communicating them by leveraging data and analytics