Data Scientist at Protege Professionals

Job Overview

• Develops data-driven solutions and insights from collated and analysed data to difficult business challenges.
• Runs analytical experiments in a methodological manner and regularly evaluate models via theoretical approaches.

Responsibilities
Develops predictive models, statistical learning models and algorithms to power data products

• Implements new statistical or other mathematical methodologies as needed for specific models or analysis
• Optimizes joint development efforts through appropriate database use and project design
• Solves business tasks using machine learning and data mining techniques
• Works with Data Engineer and Data Analyst to ensure sufficient data is being collected and is organized in a proper way for use
• Works with business users to support strategic decision making that will have a great impact to The Concept Group and its customers
• Works with stakeholders throughout The Concept Group to identify opportunities for leveraging company data to drive business solutions
• Works with Data Analytics to uncover deeper questions to explore using statistical and machine learning methods
• Builds intelligence systems that can enhance the business’ processes and products
• Provides guidance and mentorship to business and product teams on proper interpretation of data and how to test hypothesis.

Educational Qualifications, Certifications and Experience

• First Degree in a Statistics, Mathematics, Economics and other related quantitative field.
• Minimum of 6 years working experience within the data science capacity in a fast paced and complex business settings
• Experience in data mining and predictive modelling inclusive of linear and non-Linear regression, logistic regression, and time series analysis models.
• Exceptional skills in the use of MS Word, MS Excel, PowerPoint, and Outlook, all necessary for the creation of both visually and verbally engaging reports and presentations, for management and key stakeholders.

Competencies:

• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
• Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable
• Great communication skills.
• Experience with data visualization tools, such as D3.js, GGplot, etc.
• Proficiency in using query languages such as SQL, Hive, Pig
• Experience with NoSQL databases, such as MongoDB, Cassandra, HBase
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Good scripting and programming skills [Python, R]
• Data-oriented persona.

Compensation
An attractive package comprising a fixed and performance productivity pay.