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Job Summary

Data Scientist

  • Minimum Qualification: Unspecified
  • Experience Level: Mid level

Job Description

Job Purpose:

The role of the data scientist can be summarized as:

1.         Ask a question

2.         Get the data

3.         Explore the data

4.         Model the data

5.         Communicate the results/insights

With this in mind, the data scientist, will assist the company with interpreting and managing data, and to assist solving complex business problems. The data scientist will discover insights from structured and unstructured data, to help meet specific business requirements

Responsibilities:

DATA ANALYSIS      (Data mining and data analysis)

-          Discover patterns within large data sets, to assist the business in strategic development.

DATA MODELLING (Developing and assessing data models and algorithms)

-          Develop the most suitable algorithm to build a data model that will assist the business with complex problem solving.

-          Measuring the effectiveness of the data model and improving the efficiency

DATA GATHERING (Using different data gathering techniques)

-          Deploying the most effective data collecting technique to collect reliable data.

OPTIMIZATION (Using modelling to optimize stakeholder experience)

-          Deploy an effective model that can be interpreted easily and effectively by the stakeholders.

DATA ACCURACY (Develop processes and tools to monitor model performance and accuracy)

-          Ability to measure the data quality defined in the models, i.e. timeliness, completeness, consistency, accuracy, etc.

PREDICTIONS (Make accurate predictions and decisions)

-          Be able to interpret the data to assist the business to come to a conclusion and make accurate decisions.

Requirements:

Minimum 1 year working experience as Data Scientist/Analyst

Knowledge and experience in:

•           Machine Learning Tools and Techniques

•           Data Mining

•           Data cleaning

•           Data Visualization (especially using Power BI)

•           Unstructured Data Techniques

•           Cloud Tools, like Microsoft Azure and Amazon S3

•           Worked with an ERP System

•           SQL databases and database querying languages (R or Python)

•           Big Data Platforms like Hadoop, Hive & Pig

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