Where there is Data, there is Data Science. And data is everywhere today. Whatever we do on our smartphones or other gadgets, has something to do with data. Even when you shop in-store, your bill forms the data; when you go to a doctor, your prescription is data; you get admission in a college, your enrollment is data.
So, we create massive amounts of data each second with our activities. Organizations are struggling with the ways of making sense of an inordinate amount of diverse datasets.
They need to transform the ocean of data into meaningful and actionable insights that can significantly impact the tasks such as finding the best Data Science training option available to predicting the feasible treatment for diabetes or identifying the best possible solution to provide cybersecurity. This is why government agencies and businesses are looking for skilled, trained, and certified Data Scientists.
Data Scientists play a crucial role in solving vexing problems by extracting and sharing meaningful insights. They are a perfect blend of skills like computer science, statistics, modeling, analytics, and math and strong business acumen that enables them to identify the answers to significant questions that guide businesses in making the right decisions at the right time.
This article will let you know about the roles and responsibilities of a senior Data Scientist.
Who is a Data Scientist?
A Data Scientist is an analytical expert who identifies trends and manages data by utilizing technical, mathematical, and social skills. Put simply, a Data Scientist makes sense of otherwise disparate data.
A Senior Data Scientist is one who supervises the activities of a junior data scientist to provide advanced competence on mathematical and statistical concepts for the senior Data and Analytics department. A Senior Data Scientist applies advanced Data Science concepts and analytics processes to answer the major questions arising in the business processes.
Being a senior data scientist, your main role is to support pertinent stakeholders through the application of relevant advanced analytics and quantitative analytics for the key initiatives required in a business.
Responsibilities of a Senior Data Scientist
A senior data scientist plays a crucial role in the management of data, analytics of an organization. Let us discuss some of the prominent responsibilities of a Senior Data Scientist in brief.
Being a senior-level data scientist, you need to understand that you have to play a managerial role where you need to oversee the activities and tasks carried out by junior data analysts and other data workers to make sure that their activities are properly aligned with business goals. You also are required to ensure that your team is constantly developing effective working relationships and creating data-driven solutions to make the business achieve its objectives.
You play a strategic role to formulate new and innovative ideas for utilizing the huge amounts of data stored in a database. You are expected to establish scalable and accurate analytics systems across different applications.
You have to build and develop and implement the latest analytical algorithms to carry out tasks such as object detection, classification, segmentation, and recognition.
You are expected to translate business objectives into quick prototypes and enable the effective execution of data and analytics campaigns to achieve business objectives.
To design, implement, and deploy highly scalable data analytics vision and machine learning solutions is one of the primary responsibilities of a senior data scientist. You have to build and maintain a large-scale analytics infrastructure to be deployed across the business. You are also required to design, build, and implement a data management system for the analytical framework. Then, with your statistical skills, you have to refine and draw reports based on the junior data science department’s performance and analytics strategies.
This responsibility is seen with every role you play in an organization. Being a crucial responsibility, you have to work closely with junior data analysts to develop a new and improved analytics system all from prototyping to production. These systems are then sent to the senior data science department for approval.
Then you have to collaborate with senior management and stakeholders to identify and prioritize actionable insights so as to drive informed decision-making, thereby improving the business’s efficiency and productivity.
As a senior data scientist, you have to stay updated and provide actionable insights to the data science department and also the senior Data and Analytics department on directing data science and analytics best practices, design, trends, learning, and development cycles to enhance the performance of a business by providing high-quality insights.
Apart from the responsibilities mentioned above, a senior data scientist is also expected to perform the duties delegated by senior posts such as Director of Data Science, Head of Data Science, Chief Data Officer, or the recruiter.
What makes a Senior Data Scientist?
To become a senior data scientist, you must possess a bachelor’s degree in Mathematics, Statistics, Computer Science, Machine Learning, Economics, or any other related field.
A minimum of five years of experience is required working as a Data Scientist within a complex business setting. This implies that you must have experience working with natural language processing, and machine learning libraries such as OpenCV, XGBoost, sklearn, and more.
Expertise in data mining tools is also required to work with full life-cycle data science. Knowledge of popular data mining tools such as Python, R, SAS, SPSS can be greatly beneficial. You are required to master the concepts of predictive modeling that may include logistic regression, time-series analysis, linear and non-linear regression, and other popular predictive modeling algorithms.
Being at a senior level, it is thought that you already have the required knowledge and skills, but this is not so. Apart from that, you should have more in-depth knowledge to mentor junior data scientists and other data workers.
Taking up a training course is recommended as it helps you go through the path of being a senior data scientist trouble-free. Most of the training programs allow you to learn at your own pace with the learning mode of your choice. They also provide you with doubt sessions like Ask Me Anything type and guide you to get the job of your dreams.