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Data Science Job Roles In Top Fortune 500 IT Companies

Data Science is the hottest technology that has changed the cultural ethos and lifestyle of people around the world. The booming technologies in this big umbrella of data science have spanned almost all the major industry creating plentiful volume of data science jobs all over the globe. As we all know, by the impact of data science, machines have started mimicking human activities with a higher level of accuracy and is edging to a scenario where the race overtakes human intelligence. In this data driven world, the companies from across the globe collect and examine information about their clients to offer better service and enhance their bottom lines. 

Fortune 500 companies are the top-notch generation organization that people aspire to be a part of it. So, to become a data scientist in such companies is an amazing dream and even nightmare to many of us. But cracking high profile companies’ data science hiring isn’t an easy task and there is no crooked way to get into, rather it involves experience and skills of an individual to adapt to an environment where everything is a high-level techno mechanism. It entails experience and abilities, and a knack to evolve in an environment where the whole lot is high-tech. 

Henceforth, aiming a Fortune 500 IT company need a proper streamlining of the skill sets and knowledge in Data Science according to the requirement of the job roles. Obviously first phase in this process is to understand the various job roles available with the high-profile IT service providers. Some of the most sort requirement along with the Job roles available with the big players of IT is detailed herewith. 

Data Scientist

The role of Data Scientist is the most esteemed job role in almost all the industries that rely on data science. Here the Data scientists are large data wranglers, gathering and reading large sets of structured and unstructured data. A data scientist’s role combines computer technology, data processing and mathematics. They are analytical professionals who utilize their competencies in both technology and social technological know-how to discover developments and manage facts and figures. The role came to existence within the closing ten years, however has exponentially grown with time. Remarkably, agencies are paying pretty well for data scientists. The activity profile comes with superb starting salaries, excessive job pride and spiking demand in the field.

Senior Data Scientist

As a senior data analyst and commerce analyst, the candidate will play a major role in enhance the AMP commerce and payments policies. So being a member of the Analytic team, will help optimize the platform by flourishing new data products and tuning existing characteristics. They need to work on the account and payment generation flows transaction efficiency, and authorizations, and subscription management and renewals. They should deep dive into extensive data to recognise and analyse key insights or inferences that infuse product developments and business programme. The candidate to the post of senior data analyst and commerce analyst should be well-advanced in supervised and unsupervised learning, A/B testing, and causal modelling technologies and mechanisms. They should engage with business, engineering, product teams as a partner for them.

Data Engineer

The candidate is expected to layout and build records structures on MPP platforms like Teradata, Hadoop to provide efficient reporting and analytics functionality. He/she have to design solutions using new technology In-Memory Columnar databases like HANA. As a data engineer, they need to translate enlightened enterprise requirements into scalable technical answers assembly records warehousing design requirements. The candidate should have a strong knowledge of analytics desires and proactiveness to build typical infusions to enhance performance. To get into the role of data engineer in apple the candidate ought to have relevant experience in developing big data applications using the languages like Java, Spark, Hive, Oozie, Kafta, and Map Reduce is a great benefit along with great proficiency in writing Advanced SQLs, Expertise in performance tuning of SQLs.

Application Developer Data Engineer 

As an Application Developer/Data Engineer, the candidate will collaborate with software proprietors, developers, QA, project managers, support teams, and end users. The candidate is anticipated to steer evidence-of-idea and pilot implementations to demonstrate new thoughts or illustrate the use of recent technologies and the way to use it on Apple’s system. The candidate ought to be capable of carry out regular design and code critiques and participate in debugging and coding to solve issues, provide technical guidance and mentoring to a small group of software engineers, increase essential system additives as well as take the lowest line for the group’s timely deliverables quality and overall performance. For enrol into the post the candidate must be gain knowledge and experience in enterprise level application development using advanced oracle database technologies. Also, the candidate should have a strong and constructive understanding of UNIX/Linux platforms, scripting experience with Shell, XML, JSON, Advanced SQLs, Oracle PL/SQLs, and hands-on experience with big data databases for both OTLB and OLAP environment.

Machine Learning Engineer

Working as a machine learning engineer in the branch of artificial intelligence, a machine learning engineer is responsible for the creation of programs and algorithms which enable system to stimulate human intelligence. A machine learning engineer should work not only with practical aspects but should deal with theoretical data science models and assist to scale them to production-level models that can process the real-time data which is generated in every day. It’s one of the high paid job roles in top fortune companies. So, the candidate ought to have constructive skills in machine learning, statistical and programming skills. Also, any aspirants with computer engineering background can look forward to be a machine learning engineer.   

Applications Architect 

In data science, the top companies are hiring to the role of Applications architect. An application architect has job responsibilities in tracking applications, supervises their operations and progressions within the organization. They also supervise how clients are interacting with the applications developed. An application architect should be very scrupulous about the applications they design and build for their customers and also the applications should be replete with the app interface and infrastructure as designed. The competition for the position of an application architect is high and only the highly skilled ones are selected to the specified job role. Aspirants must posse’s excellent skill set in planning and should have knowledge on C++, Ajax, and LAMP. Applicants have qualification in computer science degree can appear for the job role with specified skills and industry certifications in programming and architectural designs are preferred.

Data Science Manager, XR

Roles and responsibilities of a Data Science Manager, XR is that the candidate is expected to provide world-class products by developing and leading a talented data science team. They should work in association with the engineering and outcome teams to detect trends and opportunities. The applicants ought to effectively realize the user interaction with various products and their improvement by applying their knowledge and understandings in quantitative analysis, data mining, and presentation of data. Data science managers are anticipated to generate and maintain reports, dashboards, and analysing metrics for identify and monitor the product efficiency. Managing the development of data resources along with gathering requirements, organizing sources, and supporting and launching products are other desired job roles of Data Science Manager, XR. Any aspirants qualified with degree in computer science, Maths, Engineering, Statistics, and other technical fields are preferred. Also candidates should have experience in quantitative analysis in a tech company, SQL or other programming languages, and applied statistics. Ability to initiate and drive projects with minimum guidance, experience in team management, and a knowledge of traditional or ML-based computer vision is preferred.

However, defining a career is one of the most crucial phases in an individual’s life. If it is shaped in lieu of, one’s passion the freshness of career and liveness to work with sustain throughout the career. If the passion towards Data Science is the driving force of your career, then obviously you should aim the top-notch companies where the possibility of career growth will be unlimited. For realizing this shape your skill sets and competencies to fit the requirements of the job roles of your choice.

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