Data Scientist (Python/R) - Customer Analytics

Summary about this job

Detail information about job Data Scientist (Python/R) - Customer Analytics. Terms and conditions vacancy

• INDUSTRY PIONEERS: Disrupting the market with cutting edge Customer Data Science
• CUSTOMER DATA SCIENCE: Data Engineering, DS & ML Models, Insights, Visualisation
• DATA & TECHNOLOGY: R, Python, SQL, SAS, Spark, Scala, Hadoop, Tableau/Qlikview

Our client is an industry pioneering Customer Analytics consultancy, who are disrupting the Australian market through delivering innovative, high profile, strategic projects that transform the way organisations engage and optimise experience for large customer bases. With a number of exciting new projects underway we are looking to recruit at least two more experienced Data Scientists to join the team and work across a selection of high profile financial services clients and are open to either contract or permanent applications.   

As an experienced Customer Data Scientist the responsibilities of these roles will involve but not be limited to:

• Work within a team of industry leading Data Scientists to map out the Gaming clients complex customer strategies to be optimised through Data Science and Machine Learning techniques.
• Support the financial servicesclients business stakeholders and consult around analytical project requirements and suitable discuss methodologies.
• Leverage strong programming skills in Python (or R) to manage, manipulate and model large volumes of customer data to extract and deliver strategic insights and recommendations. 
• Deliver a range of bespoke Data Science, Machine Learning, Statistical Modelling led projects leveraging techniques that may include; Linear/Logistic Regression, Confidence Interval, Test of Hypotheses, Clustering - Unsupervised & Supervised Learning, Time Series, Decision Trees , Monte-Carlo Simulation, Bayesian Statistics, Principal Component Analysis, Neural Networks, Gradient Boosting, Nearest Neighbors, (Geo-) Spatial Modeling, Recommendation Engines, Attribution Modeling, Segmentation, Predictive Modeling, Scoring Engine, Survival Analysis, Lift Modeling, Yield Optimization, Cross-Validation, Model Fitting, Experimental Design, etc.

The successful applicant will come from a strong background working in a data driven analytics and insights environment and will be able to demonstrate:

• Strong skills and experience using Python (or R) to extract, manipulate and merge large customer behaviour or transactional data sets from a variety of source systems.
• At least 3yrs commercial experience extracting 'Customer Insights' from large and complex datasets relating to; customer strategy (acquisition, retention & growth), statistical modelling, marketing campaigns or credit risk analysis, etc.
• Educated to a minimum of degree level in an analytical discipline such as - Mathematics, Statistics, Econometrics, Actuarial Studies, Data Science, Computer Science etc.
• A genuine passion to build a career in Data Analytics / Data Science, implementing analytical techniques and concepts such as; Linear/Logistic Regression, Confidence Interval, Test of Hypotheses, Clustering - Unsupervised & Supervised Learning, Time Series, Decision Trees, Monte-Carlo Simulation, Bayesian Statistics, Principal Component Analysis, Neural Networks, Gradient Boosting, Nearest Neighbors, (Geo-) Spatial Modeling, Recommendation Engines, Attribution Modeling, Segmentation, Predictive Modeling, Scoring Engine, Survival Analysis, Lift Modeling, Yield Optimization, Cross-Validation, Model Fitting, Experimental Design, etc

To apply for this position please click on the below or send your resume and cover note to [email protected]