Data Scientist

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 a number of projects in support of the business where he is required to leverage and synthesize large volumes and variety of data in order 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.

Objectives and Responsibilities of the Data Scientist

Management: The Data Scientist plays a minor managerial role where he aids in the building of the foundation of state-of-the-art scientific and technical capabilities within the Data and Analytics department in order to support several planned and ongoing data analytics projects.

The Data Scientist constantly stays on top of the industry’s trends, in order to provide forward-thinking recommendations to the business. In this capacity, the Data Scientist strives to build an in-depth understanding of the problem domain and available business data assets, especially those pertaining to strategic initiatives and value-based programs.

The Data Scientist identifies the data the business should be collecting, devises methods of instrumenting the business’s system in order to extract this information and work with other data and analytics departments to develop the processes that transform raw data into actionable business insights. The Data Scientist will also mentor supporting personnel for this position, continuously ensuring effective execution of duties at this junior level.

Analytics: The Data Scientist plays an analytical role where he designs, implements, and evaluates advanced statistical models and approaches for application in the business’s most complex issues. The Data Scientist builds econometric and statistical models for various problems inclusive of projections, classification, clustering, pattern analysis, sampling, simulations, and so forth.

In this capacity, the Data Scientist researches new ways for predicting and modeling end-user behavior as well as investigating data summarization and visualization techniques for conveying key applied analytics findings.

The Data Scientist also performs ad-hoc data mining and exploratory statistics tasks on very large data-sets related to the business’s strategies. In this capacity, the Data Scientist will also prepare reports and presentations for senior data scientists and relevant stakeholders that will give insights for departmental as well as business wide decision making.

Strategy/Design: The Data Scientist plays a strategic role in the development of new approaches to understand the business’s consumer trends and behaviors as well as approaches to solve complex business issues, for example, the optimization of product performance and gross profit.

In this capacity, the Data Scientist generates actionable insights applying advanced statistical techniques, for example, predictive statistical models, segmentation analysis, customer profiling, analysis, survey design, and data mining. The Data Scientist is responsible for cleansing of large unstructured data and enabling analytical capability in order to query the data and address various business needs.

The Data Scientist additionally uses unstructured and disjointed datasets for the purpose of independently generating actionable business insights as well as creating manageable analytical processes within the Data and Analytics department.

Collaboration: The role of the Data Scientist is not a lonely role and in this position, he collaborates with senior data scientists to communicate obstacles and findings to relevant stakeholders in an effort to improve decision making and drive business performance.

In this collaboration, the Data Scientist comes up with superb illustrations and visualizations of data that can easily be comprehended and simplified for non-technical stakeholder audiences, communicating statistical modeling results as measures of the business’s impact.

He also works 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: The Data Scientist also takes initiative to experiment with various technologies and tools with vision of creating innovative data driven insights for the business at the quickest pace possible. In this position, the Data Scientist also takes initiative in evaluating and adapting new and improved data science approaches for the business, which he forwards to senior management of approval.

Other Duties: The Data Scientist also performs similar duties and duties as assigned by the Senior Data Scientist, Head of Data Science, Director Science, Chief Data Officer, or the Employer.

Required Qualifications of the Data Scientist

Education: The Data Scientist has to have 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.

Experience: A candidate 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 support data scientist junior support personnel.

The candidate will also have experience working in probability and statistics, time-series analysis, or econometrics as well as experience in the use of machine learning methods, for example, linear regression, correlation, statistical significance, and so forth. A candidate for this position will also require strong programming skills and experience working with tools such as SAS, R Programming, Open Source, visualizations, and so forth.

A suitable candidate will also have had 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: Communication skills for the Data Scientist, both in written and verbal form are a must have. The Data Scientist will be required to explain advanced statistical content to senior data scientists and relevant stakeholders.

Therefore, he must have the ability to translate and tailor this technical content into business applicable material with clear recommendations and insights relevant to the audience at hand.

These reports and presentations will not only be translations of technical analyses into business applicable material, the reports have to be simple, concise, understandable and convincing, which will require exceptionally good communication skills on the Data Scientist’s part.

Ms Office/Software: A suitable candidate will demonstrate proficiency in the use of Ms Word, Ms Excel, PowerPoint, and Outlook, which will be necessary for the creation of both visually and verbally engaging reports and presentations, for senior data scientists and key stakeholders. He must also have demonstrated skills in SQL server reporting services, Salesforce, analysis services, integration services, Tableau, or other data visualization tools.

Technological Savvy/Analytical Skills: A candidate for this position must be technologically adept, demonstrate exceptionally good computer skills, and demonstrate a passion for research, statistics, and data analysis as well as a demonstrated ability and passion for designing and implementing successful data analysis solutions within a business.

The candidate must have a strong understanding of data-mining techniques and an ability to apply these techniques in practical real-world business issues. The Data Scientist will demonstrate an ability to consider data, identify patterns, issues, or data analysis needs for the business. The candidate must also have skills in the workings of SQL and scripting languages such as Python and Perl as well as familiarity with statistical analysis, data visualization, and data cleansing tools and techniques.

He will additionally demonstrate strong skill in statistical techniques inclusive of cluster-analysis test design, regressions, and forecasting methodologies as well as substantial familiarity in big data and standardizing and A/B testing.

Interpersonal Skills: The candidate must also demonstrate personal attributes that will qualify him for the position, for example, he will have 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, have an ability to work on multiple projects and meet tight deadlines, have exceptional problem solving skills, and remain calm and composed in times of stress and uncertainty.

People Skills: The Data Scientist must also 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.

Career path