Description
Our client, a global financial service company are looking for an interim Data Scientist for a 12 month contract.
Responsibilities:
* Participate in solutioning efforts to define and develop Data and Statistical Modelling components, that interoperate seamlessly with existing Talent, Reward and Performance business systems and can be leveraged by Consulting teams to add value to Client Engagements. Leverage Data Visualization techniques and tools to effectively demonstrate patterns, outliers and exceptional conditions in the data. Leverage Data from across the Talent, Rewards and Performance business and as necessary, source and integrate public data. Focus on design and execution of data-centric business problems, and in the process create unique analytical solutions comprising (Big) Data management, supported by advanced analytical techniques (eg, R, machine learning, neural networks, A/B testing, etc). Generate and test working hypotheses, prepare and analyze historical data, identify patterns from samples for reporting of trends and support Predictive Analytics. Conceptualize necessary Data Governance models to support the technical solution and assure the veracity of the data. Work collaboratively with other members of the Data, Analytics and Reporting (and IT) teams to innovate and create compelling data-based stories and experiences. Ensure Models developed can be leveraged and sold to generate revenue by Consulting teams
Masters/Ph.D. in Computer Science, Statistics, Engineering or similar technical field and 2-3+ years experience in a relevant role. Well versed at applying advanced analytical techniques to large and varied data sets, generated and flowing at a rapid rate.
Sample techniques include, but are not limited to:
o Applied machine learning and natural language processing
o Collaborative filtering and recommender systems
o Social network analysis and statistical text mining
o Neural networks
o Data visualization (QlikView/Tableau)
o Data mining and predictive modelling. Deep knowledge of Statistical Modelling, using R, SPSS or Alteryx.
* Proficient with programming languages supported by a big data platform, like .NET, Python, C++, or ECL, etc.