The Data Scientist is responsible for advising the business on the potential of data, to provide new insights into the business’s mission, and through the use of advanced statistical analysis, data mining, and data visualization techniques, to create solutions that enable enhanced business performance.
The Data Scientist also plays a leading role in the management of several projects in support of the business where he/she is required to leverage and synthesize large volumes and variety of data to enhance the business’s understanding of individual population segments, propensities, outcomes, and decision points.
The Data Scientist combines data, computational science, and technology with consumer-oriented business knowledge in the business setting, to drive high-value insights into the business and drive high-impact through the business levers at the business’s disposal.
- Play a managerial role and aid in the building of the foundation of state-of-the-art scientific and technical capabilities within the Data and Analytics department.
- Stay on top of the industry’s trends, to provide forward-thinking recommendations to the business.
- Identify the data the business should be collecting, devise methods of instrumenting the business’s system to extract this information and work with other data and analytics departments to develop the processes that transform raw data into actionable business insights.
- Design, implement and evaluate advanced statistical models and approach for application in the business’s most complex issues.
- Build econometric and statistical models for various problems inclusive of projections, classification, clustering, pattern analysis, sampling, simulations, and so forth.
- Prepare reports and presentations for relevant stakeholders that will give insights for departmental as well as business-wide decision making.
- Strategy/Design: Play a strategic role in the development of new approaches to understand the business’s consumer trends and behaviours as well as approaches for solving complex business issues.
- Work closely with other the data analytics team, data warehouse engineers, data engineers, product managers, the IT department, and other informatics analysts across the business in solving complex business issues.
- Knowledge: Experiment with various technologies and tools with the vision of creating innovative data-driven insights for the business at the quickest pace possible.
- A bachelor’s degree in Statistics, Mathematics, Computer Science, Machine Learning, Economics, or any other related quantitative field. Working experience of the equivalent is also acceptable for this position.
- Must have had at least 3 years of working experience working with business analysis/informatics and business outcomes research within a fast-paced and complex business setting, preferably working as a support data scientist.
- Experience working in probability and statistics, time-series analysis, or econometrics as well as experienced in the use of machine learning methods, e.g., linear regression, correlation, statistical significance, and so forth.
- Strong programming skills and experience working with tools such as SAS, R Programming, Open Source, visualizations, and so forth. Experience as well as in-depth knowledge of the Python programming language, SAS Enterprise Miner and substantial knowledge of big data platforms such as Aster and Hadoop.
- Communication skills, both in the written and verbal form are a must-have. The ability to translate and tailor technical content into business applicable material with clear recommendations and insights relevant to the audience at hand.
- An ability to work effectively in a group/collaborative setting, be result-oriented, be highly analytical, be a strategic and creative thinker, have superior organizational skills, have a strong attention to details, can work on multiple projects and meet tight deadlines, have exceptional problem-solving skills, and remain calm and composed in times of stress and uncertainty.
- Must be a people person, demonstrating an ability to create and maintain strong, meaningful, and lasting relationships with others. He must also be a confident but friendly and approachable individual who will inspire confidence and trust in his seniors and key stakeholders, leading them to give credit to his insights and judgments.
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