Key Roles and Responsibilities :
Collaborate with business stakeholders to identify opportunities for leveraging data to drive business solutions
Research, design, implement and deploy scalable data analytics vision and machine learning solutions to challenge complex business issues
Extending company’s data with third party sources of information when needed
Enhancing data collection procedures to include information that is relevant for building analytic systems
Processing, cleansing, and verifying the integrity of data used for analysis, and building algorithms necessary to find meaningful answers
Perform analysis using programming languages or statistical packages such as Python and R etc.
Mine and analyze data to drive optimization and improvement of business strategy
Architect scalable and highly available applications leveraging the latest tools and technologies
Creatively visualize and effectively communicate results of data analysis, insights, and ideas in a variety of formats to key decision-makers within the business
Take ideas to successful launch by leading and mentoring diverse, geo-distributed teams through innovation, bootstrapping, pilot, production, scaling, and maintenance phases with multiple stakeholders to the highest levels of quality and performance
Develop SQL Queries for reports and dashboards
Analyze relational and transactional databases to provide data analysis, and present results in a clear manner
Create documentation around processes and procedures and manage code reviews
Apply industry standards best practices to development activities
Work on data set to ensure solutions are successfully executed, within agreed upon time frames
Knowledge, Skills, and Attributes :
Subject matter expertise in data modeling
Theoretical understanding of statistical methods and machine learning techniques
Ability to thrive in a dynamic, fast-paced environment
Excellent quantitative and qualitative analysis skills
Strong desire to acquire more knowledge in order to keep up to speed with the ever-evolving field of data science
Strong curiosity to sift through data to find answers and more insights
Solid understanding of the information technology industry within a matrixed organization and the typical business problems such organizations face
Ability to clearly and fluently translate technical findings to non-technical team business stakeholders to enable informed decision-making
Ability to create a storyline around the data to make it easy to interpret and understand
Theoretical understanding of statistical methods and machine learning techniques
Self-driven and able to work independently, yet acts as a team player
Able to apply data science principles through a business lens
Strong desire to create strategies and solutions that challenge and expand the thinking of everyone around you
Ability to think strategically about how to use data to drive competitive advantages
Academic Qualifications and Certifications :
Degree in Data Science, Business Analytics, Mathematics, Economics, Statistics, Engineering, Computer Science, Computer Engineering or another quantitative field (preferably a bachelor’s degree or equivalent)
Relevant programming qualifications and / or certifications
Relevant Agile certification is preferable
Required Experience :
Demonstrable experience with one or more programming languages (e.g. Python), statistical packages (e.g. R), and database languages (e.g. SQL)
Demonstrable experience with data warehouse and data lake technical architectures, infrastructure components, ETL / ELT, and reporting / analytic tools
Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc. (excellence in at least one of these is highly desirable)
Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc
Demonstrable experience in data modeling
Demonstrable experience applying statistical methods and machine learning techniques to solve business problems
Experience with distributed data / computing tools such as Map / Reduce, Hadoop, Hive, Spark, MySQL, etc.
Experience in working in micro-services architecture working with APIs development
Demonstrable experience of full-stack software development with prolific coding abilities
Demonstrable experience in Elastic search, Scoring, and recommendation on very large volumes of data
Experience with Agile Development Methodologies and Test-Driven Development
What will make you a good fit for the role?
2-3 years experience.
Tertiary qualifications (a Masters or PhD degree) in a quantitative discipline, such as Statistics, Econometrics, Applied Mathematics, Engineering, Applied Science.
or equivalent highly desired.
At least one of the following modelling software packages : MATLAB, R, SAS, SPSS.
At least one of the following scripting languages : C++, Java, Python.
Data visualisation using Tableau / Qlikview / D3.js
Demonstrating your ability to adapt quickly and manage an environment of rapid change and development,and lead others through this process 
