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Data Scientist

Job Industry:

IT Internet and Technology - Marketing, PR and Web Design

Job Location:

Gibraltar

Job Description:

RecruitGibraltar are currently helping our client who is a long established and reputable gaming company who offer long term career growth, excellent salary, relocation assistance, and a rewarding working environment where you can make a real impact. They are looking for a Data Scientist to be responsible for the delivery of machine learning algorithms, optimization solutions, complex quantitative analysis and a variety of custom data processes and tools

What is the plan for the Data Scientist role?

The key focus is to identify opportunities for predictive analytics and optimization across the business, present ideas, propose analytics / solution approach, gather, explore, cleanse, integrate and analyse data from large operational transactional datasets and external online sources, conduct statistical data exploration and quantitative analysis, assess data quality, share and verify key findings with business, apply supervised and non-supervised machine learning algorithms, fine tune models, test and validate models, build optimisation engines, assess key model characteristics and overall impact, re-iterate certain phases of the process if necessary, assist to implement solution into production environment, educate business stakeholders on model output, impact and behaviour, assist / coach along the business process transformation lifecycle.

What will you do as a Data Scientist?

Define, build and verify machine learning solutions, optimization engines and statistical models to maximize business value in Acquisition, Product management, CRM, Trading, Responsible Gambling, Finance and VIP management
Use supervised machine learning approaches to exploit predictive value from large internal transactional datasets and external data sources
Apply non-supervised machine learning approaches, advanced statistical and analytical
Understand how advanced analytic technique and application, such as decision trees and clustering techniques can help to solve business problems
Enhance overall customer behavioural profile and improve organizational capability for optimized next best action
Chose the best modelling approach for given business problem
Identify target variable, define need for input data
Conduct data preparation to integrate data from heterogeneous sources and prepare data ready for modelling / analysis
Apply multivariate analysis to understand variables predictive power
Use advanced data manipulation and creativity to invent new features that boost model performance
Apply clustering algorithms to enhance customer behavioural segmentation
Fine-tune model performance for best business benefit
Compile an analytical plan for given business problem
Define hypothesis/null hypotheses to be tested
Monitor live model performance, apply statistical process control approaches to identify significant performance deviation and need for intervention / model refresh
Develop algorithms that personalize content or automate actions at various customer touch points
Build custom solutions around real-time event streams and stream analytics
Exploit opportunities around Big Data technologies and cloud processing
Interact with business stakeholders to identify key opportunities for predictive analytics and optimization
Gain agreement and support for analytical approaches and solutions amongst business stakeholders
Articulate model characteristics and impact to business stakeholders efficiently, with less emphasis on technical details and more focus on commercial implications
Educate business users and leaders on how to interpret and use model output
Drive analytical projects through to delivery and embed them within the organisation, advocate predictive analytics to transform operational business processes
Identify potential new external data sources that can enhance data, assess value, build prototype data feeds / data collection processes and conduct proof of concept for data usability

What do you know that makes you a great Data Scientist?

BSC in computer science, mathematics or statistics
Experience of data analytics at a senior level
A true talent in working with data
Experience with modelling platforms R, Python, Knime, Statistica, SAS Miner or Stat, XLStat
A balanced set of expertise across a number of domains including supervised and unsupervised machine learning techniques, data engineering, statistical analysis, custom tools development and business consulting.
Strong understanding of the data mining methodology i.e. Crisp DM, SEMMA
Experience in building models of decision trees, neural networks, random forests, logistic and linear regression, text mining, clustering, ensemble models, uplift modelling
Methods for Validating Models: mean squared error, R squared, Confusion matrix, gains, ROC
Expert data manipulation skills SQL, analytical functions, query optimization, Python automation
Experience in Big Data environments (MS Azure, Spark, Hive) and/or stream analytics
Good understanding of business processes within online gaming
Strong understanding and experience working with large transactional data sets, e.g. bet records, site visitor data, transformation and analytics conducted over billions of records
Strong application of descriptive analytics and statistical techniques
Strong presentation skills, able to simplify and articulate complex domain areas to senior stakeholders.


Salary Up to 55k based on experience with bonus, an excellent relocation package and private healthcare.

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