The Definitive Guide to Transition Your Career From Software Developer to Data Scientist in 2019

by | Aug 13, 2019

We generate over 2.5 quintillion bytes of data every day on the internet, inside our business organizations and while using various electronics and digital devices like phones, computers, watches, cars, machinery, and various other gadgets.To process and present this data in a way that can help business decision making we need data scientist. Becoming a data scientist is amongst the most lucrative career option for the modern world.

As you know it, everyone is busy constantly producing videos, audio, text, graphics, presentation and various other content to interact, engage and convert people into paying customers — companies across Digital, FMCG, Finance, Manufacturing, Retail, Technologies are looking at these data to turn it into information and insights. The indomitable success of new economy companies like Google, Facebook, Tesla, LinkedIn, etc. are largely dependent on how they can convert the accumulated data to drive actions to guide people.

The unprecedented accumulation of data coupled with the high demand for data analysis needs globally by leading businesses, governments and innovators have fuelled the exponential demand for skilled data science professionals. Data scientist job postings as a share of all postings on Indeed jumped a full 31% in December 2018, compared with the same period in December 2017. Most major job portals have seen a similar rise in the job postings for data scientist position. However, the availability of skilled professionals doesn’t match the demand.

The purpose of this guide is to help you with actionable insights which you can use for deciding to transit yourself as a data scientist or in data science field opportunities. This guide will help you in deciding that if you are a software developer aiming to pursue more lucrative career opportunities, to help you earn a better salary, get into a more meaningful career and future-proof your career.

How Companies are using Data Science?

You make up to this point simply means that you have a deep interest in exploring the career options and roles available for data scientists.

Business Intelligence (BI) Developer

In a constantly changing economic landscape, businesses are in search of finding the emerging trends, competitive landscape and opportunities that they can tap to survive and thrive. You can present yourself as a Business Intelligence Developer provided you have the interests, skills and personality for the following:

    • Expert in gathering requirements & translating business requirements into technical solutions.
    • You know the techniques required for data visualization design, development and integration.
    • Capabilities to implement BI projects from start to finish.
    • You’ve developed expertise for using DAX query for building complex formulas/measures such as creating dynamic chart headers as per the filter selection, you have got SQL skills for writing custom queries to aggregate and extract data, database design and architecture.
    • As a BI developer, you will be required to present the outcome to the business users. You must have good written and oral communication skills to build a relationship with the stakeholders.
    • Ability to understand the business context and apply analytical concepts to provide business solutions.

Data Architect

As a Data Architect you will be involved in providing an idea data management solution for the projects. You will be expected to be functionally knowledgeable in multiple Big Data and NoSQL Technology areas and hands-on in data management and programming. You will provide solution architecture for the business problem, platform integration with third party services, designing and developing complex features for business needs.

      • You will also be expected to show your capabilities for leadership, mentorship, systems analysis, architecture, design, configuration, testing, debugging, and documentation.
      • Own and drive the evaluation, adoption, design and architecture Big Data technology.
      • Work with Product Owner/Business Analysts to understand functional requirements and interact with other cross-functional teams to architect, design, develop, test, and release features.
      • Develop Proof-of-Concept projects to validate new architectures and solutions.
      • Drive common vision, practices and capabilities across teams.
      • Engage with business stakeholders to understand required capabilities, integrating business knowledge with technical solutions.
      • Engage with Technical Architects and technical staff to determine the most appropriate technical strategy and designs to meet business needs.

Applications Architect

In the application architect role, you will work on a variety of projects and will play a key part in making sure that end results are designed according to the planned goals, relevant patterns and analyses.

      • You will be required to design and implement solutions getting involved in setting up the Logical and Physical Architectures.
      • Ensure that the project and solution assumptions made during project planning and scoping are validated.
      • Comprehend business strategies and requirements and develop necessary designs and plans to ensure projects and solutions satisfy those needs.
      • Participate and own the Functional Requirements Document and Specification, directly contribute to the Technical Requirements Document.
      • Act as a contributing member of the project team from project inception to completion.
      • Ensure functionality is consistent with project requirements.
      • Collaborate with project managers and other staff members to develop budgets and timelines for solutions.
      • Maintain balance between requirements and efficient solutions.
      • Track the behavior of applications used within a business and how they interact with each other and with users.

Infrastructure Architect

Oversee that all business systems including the data center, software and applications are working at acceptable performance level and can support the development of new technologies and system requirements.
You will be responsible for design, development, implementation, operation improvement and debug for public and private Cloud Management.

Data Scientist

To attract the employer to hire you as a Data Scientist and continue to remain relevant for the job, you will need to have the following key skills:

      • Complete knowledge and experience in data science and use of statistical methodologies.
      • Experience capturing, assessing and making recommendations, including reviewing data for completeness and consistency, analyzing and interpreting data.
      • Developing and analyzing data using machine learning methods and techniques such as clustering, regression, optimization, recommendation, neural networks, and others.
      • Strong quantitative and analytical skills with experience with data science tools using Python, R, Scala, Julia, or SAS.
      • Understanding of data science disciplines such as mathematics, statistics, computer science, physics, and other related fields.
      • Familiarity with using cloud services and Big Data tools to develop data science solutions.

Data Analyst / Data Engineer

As a Data Analyst, your employer will desire that you have good business and product knowledge; especially in the area of Data management, design, architecture and dashboard development.
You are expected to possess good command over the written and verbal communications skills and presentation skills.
You must be aware of the best practices for industry data management, tools, and processes for data management, data warehouse and report development.
Must have good programming skills in Python, Java, R or other statistical programming tools.

Machine Learning Specialist / Engineer

Since Machine Learning is the core of Data Science, the specialists play a vital role in leading and contributing to define an overarching big-data-driven approach to advanced analytics strategy and architecture.

      • You will influence the strategic direction by identifying opportunities in large, rich data sets and creating and implementing data-driven strategies that deliver the results. Create visualizations to connect disparate data, find patterns and tell engaging stories.
      • Working with business domain, IT and data experts to identify detailed data needs, sources, and structure to support solution development and deployment.
      • Develop methods for preparing analytical datasets for model development, documentation, implementation, and validation.
      • Deploy statistical/machine learning models into a platform or application.

Statistician

If you have got the flare for math and statistics, you can use it to help businesses analyze business challenges to be solved, develop analytical models, evaluate alternatives and identify solutions. As a statistician working for the Data Science team you will be expected to deliver the following:

    • Collaborate with team members to lead research studies and ensure that the appropriate statistical models are designed and developed for the given project.
    • Contribute for optimizing the design, analysis, interpretation of results and conclusions for research related studies and trials.
    • Deploys a range of scientific, mathematical, computational and/or data analysis methods for developing technologies.
    • Documents and maintains a process for developing statistical analysis plans and applying the appropriate models as per the study design.

What’s are the Career Options in Data Science

You make up to this point simply means that you have a deep interest in exploring the career options and roles available for data scientists.

Business Intelligence (BI) Developer

In a constantly changing economic landscape, businesses are in search of finding the emerging trends, competitive landscape and opportunities that they can tap to survive and thrive. You can present yourself as a Business Intelligence Developer provided you have the interests, skills and personality for the following:

  • Expert in gathering requirements & translating business requirements into technical solutions.
  • You know the techniques required for data visualization design, development and integration.
    Capabilities to implement BI projects from start to finish.
  • You’ve developed expertise for using DAX query for building complex formulas/measures such as creating dynamic chart headers as per the filter selection, you have got SQL skills for writing custom queries to aggregate and extract data, database design and architecture.
  • As a BI developer, you will be required to present the outcome to the business users. You must have good written and oral communication skills to build a relationship with the stakeholders.
  • Ability to understand the business context and apply analytical concepts to provide business solutions.

Data Architect

As a Data Architect you will be involved in providing an idea data management solution for the projects. You will be expected to be functionally knowledgeable in multiple Big Data and NoSQL Technology areas and hands-on in data management and programming. You will provide solution architecture for the business problem, platform integration with third party services, designing and developing complex features for business needs.

  • You will also be expected to show your capabilities for leadership, mentorship, systems analysis, architecture, design, configuration, testing, debugging, and documentation.
  • Own and drive the evaluation, adoption, design and architecture Big Data technology.
  • Work with Product Owner/Business Analysts to understand functional requirements and interact with other cross-functional teams to architect, design, develop, test, and release features.
  • Develop Proof-of-Concept projects to validate new architectures and solutions.
  • Drive common vision, practices and capabilities across teams.
  • Engage with business stakeholders to understand required capabilities, integrating business knowledge with technical solutions.
  • Engage with Technical Architects and technical staff to determine the most appropriate technical strategy and designs to meet business needs.

Applications Architect

In the application architect role, you will work on a variety of projects and will play a key part in making sure that end results are designed according to the planned goals, relevant patterns and analyses.

  • You will be required to design and implement solutions getting involved in setting up the Logical and Physical Architectures.
  • Ensure that the project and solution assumptions made during project planning and scoping are validated.
  • Comprehend business strategies and requirements and develop necessary designs and plans to ensure projects and solutions satisfy those needs.
  • Participate and own the Functional Requirements Document and Specification, directly contribute to the Technical Requirements Document.
  • Act as a contributing member of the project team from project inception to completion.
  • Ensure functionality is consistent with project requirements.
  • Collaborate with project managers and other staff members to develop budgets and timelines for solutions.
  • Maintain balance between requirements and efficient solutions.
  • Track the behavior of applications used within a business and how they interact with each other and with users.

Infrastructure Architect

Oversee that all business systems including the data center, software and applications are working at acceptable performance level and can support the development of new technologies and system requirements.
You will be responsible for design, development, implementation, operation improvement and debug for public and private Cloud Management.

Data Scientist

To attract the employer to hire you as a Data Scientist and continue to remain relevant for the job, you will need to have the following key skills:

  • Complete knowledge and experience in data science and use of statistical methodologies.
  • Experience capturing, assessing and making recommendations, including reviewing data for completeness and consistency, analyzing and interpreting data.
  • Developing and analyzing data using machine learning methods and techniques such as clustering, regression, optimization, recommendation, neural networks, and others.
  • Strong quantitative and analytical skills with experience with data science tools using Python, R, Scala, Julia, or SAS.
  • Understanding of data science disciplines such as mathematics, statistics, computer science, physics, and other related fields.
  • Familiarity with using cloud services and Big Data tools to develop data science solutions.

Data Analyst / Data Engineer

As a Data Analyst, your employer will desire that you have good business and product knowledge; especially in the area of Data management, design, architecture and dashboard development.
You are expected to possess good command over the written and verbal communications skills and presentation skills.
You must be aware of the best practices for industry data management, tools, and processes for data management, data warehouse and report development.
Must have good programming skills in Python, Java, R or other statistical programming tools.

Machine Learning Specialist / Engineer

Since Machine Learning is the core of Data Science, the specialists play a vital role in leading and contributing to define an overarching big-data-driven approach to advanced analytics strategy and architecture.

  • You will influence the strategic direction by identifying opportunities in large, rich data sets and creating and implementing data-driven strategies that deliver the results. Create visualizations to connect disparate data, find patterns and tell engaging stories.
  • Working with business domain, IT and data experts to identify detailed data needs, sources, and structure to support solution development and deployment.
  • Develop methods for preparing analytical datasets for model development, documentation, implementation, and validation.
  • Deploy statistical/machine learning models into a platform or application.

Statistician

If you have got the flare for math and statistics, you can use it to help businesses analyze business challenges to be solved, develop analytical models, evaluate alternatives and identify solutions. As a statistician working for the Data Science team you will be expected to deliver the following:

  • Collaborate with team members to lead research studies and ensure that the appropriate statistical models are designed and developed for the given project.
  • Contribute for optimizing the design, analysis, interpretation of results and conclusions for research related studies and trials.
  • Deploys a range of scientific, mathematical, computational and/or data analysis methods for developing technologies.
  • Documents and maintains a process for developing statistical analysis plans and applying the appropriate models as per the study design.

What Do Data Scientists Do and What Skills Do You Need to Become a Data Scientist?

If you have gone through the above job role specifications for the various positions that businesses hire data science professionals, you will find that their primary responsibility is to extract meaning from the data. They require skills and experiences to present insights to help steer strategic business decisions which require both tools and methods from statistics and machine learning, as well as use human intelligence. You as a data science professional will spend a substantial amount of time in the process of collecting, cleaning, and processing data. To achieve your goal of converting data into meaningful insights you will be expected to apply persistence, statistics, and software engineering skills, and debugging techniques.

Mathematics Expertise

You will require the ability to view the data through a quantitative lens. Using the mathematical models and statistical methods, you can establish the correlation between various data sets and express it mathematically. Having a strong mathematical and statistical foundation for visualizing the solutions to many business problems. You’d be at an advantageous position if you know these mathematical and statistical methods:

  • Logarithm, exponential, polynomial functions, rational numbers.
  • Basic geometry and theorems, trigonometric identities.
  • Real and complex numbers and basic properties.
  • Series, sums, and inequalities.
  • Graphing and plotting, Cartesian and polar coordinate systems, and conic sections.

Software Engineering Skills

As a data scientist, you will be dealing with the programming skills to gather, extract, clean and present data in a meaningful way. A good programming skill will help you deliver better result:

  • Your ability to develop software in a way that it can be used by others, including documentation, installing packages, configuration management, debugging and running computational studies.
  • Creating technical specifications. Creating, updating, and sharing a project using version control tools.
  • Programming in Python using the Python scientific stack, including libraries, APIs and other tools.
  • Developing unit tests and using test-driven development to build software.

You can learn more about how to become a better software developer here.

Business Problem Solving

You will be dealing with complex business challenges being faced by the business today. You’ll be working together with the business and operation management team to understand data, pattern, and insights that they are looking for to make the decision. Your ability to quickly understand the business environment and translate observations to shared knowledge, and contribute to strategy on how to solve core business problems will determine largely the success that business derives from the data science. Your usefulness will be proven by leveraging the tech, algorithms, data management and analytics capabilities to build insights that deliver the strong business value proposition.

Machine Learning Skills

Having proficiency in machine learning techniques will help you solve different data science problems which are dependent on predictions of outcomes.

You’ll find yourself at an advantage position if you possess machine learning skills like neural networks, reinforcement learning, adversarial learning, supervised machine learning, decision trees, logistic regression, unsupervised machine learning, Time series, Natural language processing, Outlier detection, Computer vision, Recommendation engines, Survival analysis, Reinforcement learning, and Adversarial learning.

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