How to Get a Government Job as a Data Scientist?

01-Feb-2022

The world now runs at an unprecedented rate with the evolution of technology backed by the internet and the ensuing internet of things (IoT). With the increasing adoption of innovations across varied sectors, the government sectors have also joined the crowd. 

A growing number of government organizations have shifted towards electronic databases from paper records. Thus, the demand for scientists is ever-growing to make intelligent exploitation of the ever-growing data adoption and its application.

To get a data science job in government entails knowing the intrinsics of how data science is applied in the governmental sector. 

How Data Science Help Government?

The government, more than any other sector, is in desperate need of analytical minds, innovative ideas, and the fortitude to sort through and make sense of large data sets. Government agencies rely largely on qualified data scientists to assist them to make educated and far-reaching choices that influence the lives of millions of people as one of the largest data collectors in the country—from census data to national security intelligence. 

A data science profession in government may be the appropriate choice for you if the prospect of applying your data science talents to contribute to a country's health, prosperity, and security pique your interest.

What is the Role of Data Science in Government?

The ultimate goal of data science in government is to extract real-time actionable insights from data obtained, which is similar to the purpose of data science in other domains. However, there are so many different organizations that fall under the banner of government—from law enforcement and intelligence agencies like the CIA and FBI to federal and state departments. Data scientists have a wide range of opportunities.

On the social front, data scientists collaborate with municipalities and cities to increase efficiencies and cost savings, assess the impact of government efforts, and discover possibilities to promote community involvement and safety.

Considering the vast amounts of data generated across agencies, counties, and towns, government data science opens up a sandbox of prospects for diagnosing, preventing and resolving many of the issues that plague entire communities.

Can a Data Scientist Work in Government?

There is no limit to where data science can function in this data-driven world. Most data scientists bring technical skills like probability and statistics, Python and SQL, data visualization, machine learning, and AI understanding to the table. Many government roles, such as agriculture, environment, climate, consumer affairs, education, military, economics, and urban development and housing, also require sector-specific domain knowledge.

Since, in comparison to other sectors, a major portion of government records are either handwritten or exist in an analog form, data scientists in government typically spend a significant amount of time cleaning information and processing it to a usable state. This gives data scientists fascinating chances to apply algorithms and machine learning methods to datasets that have never been wrangled before.

Data scientists have massive roles to play in the government sectors including the following responsibilities:

  • Identifying and preventing wastage, fraud, and abuse through analyzing spending data.
  • Leveraging business intelligence to assist all levels of government in making better financial decisions.
  • Collaborating with researchers on studies and keeping track of results that could influence the development of new medications and consumer products.
  • Defense intelligence collection and analysis to improve defense systems.
  • Coordinating data collection, analysis, and modeling with state and municipal departments.
  • To explain data findings, use maps and visuals.
  • Developing and presenting data-driven suggestions to non-technical government officials.

How to Get a Data Science Job in Government Sectors?

The first and foremost thing to get a data scientist position in the government sector is to qualify for the position, which entails having the right qualification and possessing the skills and talent. 

To work as a data scientist, you'll need a bachelor's or master's degree in a related field like business information systems, mathematics, statistics, economics, computer science, or information management.

A master's degree in data analysis or data science is the most common qualification for a data scientist. M.Sc. in Data Science, M.Sc. in Business Analytics, M.Sc. in Data Science and Analytics, and M.Sc. in Big Data are just a few of the popular postgraduate qualifications available.

The following are a prerequisite for an aspiring individual to get a data science job in government sector. 

  • Intern at any company that specializes in data science.
  • Take online data science classes as well as courses in statistics, probability, and linear algebra.
  • Learn the fundamentals of NLP, data extraction, computer vision, bioinformatics, and speech processing, among other topics.
  • Investigate the fields of optimization, information theory, and decision theory.
  • Obtain any professional qualification in data science.
  • Try database management, data analysis, or database design.

What are the Top Data Science Job in Government at the Global Level?

Data science is a worldwide sector that is rapidly expanding. Data science has permeated every profession, from healthcare and public health to business and law enforcement, resulting in a huge necessity for well-trained data science professionals. Government data science careers are accessible in nearly all of the federal government's departments and agencies.

CIA: The CIA is one of the most difficult federal agencies to work for, yet it gives data scientists plenty of chances to influence the result of regional, national, and events around the world. Data scientists working for the CIA face major challenges in their daily duties, ranging from diplomatic stability analysis to counterterrorism, and must frequently work quickly to analyze data and issue findings in order to provide guidance to other agencies, along with other law enforcement agencies. The CIA offers competitive pay and benefits, as well as a government pension.

FBI: Data scientists working at the Federal Bureau of Investigation have a wealth of opportunities to put their abilities to use, many of which are quite difficult. Law enforcement data scientists analyze and quantify massive volumes of data on everything from white-collar crime to kidnapping rings for children. Data scientists working for and with the FBI are well rewarded, with excellent benefits and annuity options, like with most government institutions.

NASA: NASA hires data scientists who deal with data on a number of initiatives, making it a good opportunity for data scientists with a flair for the physical sciences. NASA collects and analyses atmospheric, oceanic, and forestry data in addition to astronomy-related activities. NASA data scientists may also examine data pertaining to technology initiatives and programming. NASA data scientists may examine satellite photos and data and utilize the information to generate maps and models for expedition and research projects. They might also look into seasonal rainfall and how they link to other meteorological and climate events like volcanic eruptions.

NOAA: The National Oceanic and Atmospheric Administration collect and analyses meteorological, water, and atmospheric data from across the world. NOAA's work, which includes making recommendations to national and international government agencies on disaster and hunger avoidance related to weather systems and climate change, relies heavily on data scientists. NOAA data scientists may also construct severe weather, forecasting models. They can examine the outcomes of various models and adjust algorithms when new data becomes available. Their findings could have an impact on other federal agencies' planning and readiness activities, such as the Department of Homeland Security and the Department of Transportation.

For data scientists intrigued in implementing data science to earth and physical science subjects and challenges, as well as making a worldwide influence in the age of climate change, the NOAA is a great choice.

Data Science Job in Government of India

Data science intervention is becoming particularly crucial in countries like India, where the population is high and human data management is time-consuming and labor-intensive. With burgeoning tech firms and educational institutions in India, data science is already booming. Consequently, there has been an increase in the number of data science employment postings. As the government sector transitions to digital, data science government employment is gaining traction in the country.

A few of the popular Data science jobs in the government sector in India

THSTI: Data scientist
THSTI hiring applications are accepted online for various assistant positions using the THSTI authorized form. The data scientist would be hired by THSTI Andra Pradesh on a central government premise. A preliminary interview will be done. Those that succeed will be put on a shortlist and directed to THSTI.

Required qualifications:

  • Based on the job profile they are applying for, the candidate should have basic qualifications such as 10th grade, ITI, MBBS, and PG Degree/Diploma (Relevant discipline).
  • One should be between the ages of 18 and 54.
  • They must pass written tests, interviews, and document verification in order to be accepted into the THSTI.
  • The selected candidates for the THSTI position will be subjected to an official verification process.

NABARD- Chief Data Consultant cum Analytics

NABARD will shortlist individuals in a 1:10 ratio based on qualifications, experience, and other factors. Following the selection, the shortlisted candidates' roll numbers will be posted on the bank's website. An interview and subsequent selection procedure will be conducted with the candidates who have been shortlisted. The ultimate appointment will be made in accordance with the decision of the selection panel that was formed specifically for this reason.


Qualifications:

A bachelor's degree in computer science, engineering, mathematics, or statistics is required of the candidate.

He or she should have a minimum of seven years of expertise in areas such as data analytics, artificial intelligence, machine learning, and business intelligence tools for graduates and five years for postgraduates.

The candidate must be under the age of 62.

ReBIT: Senior Data Scientist recruits senior data scientists to analyze huge volumes of raw data for patterns, choose algorithms/models, construct AI/ML products, extract insights, and optimize algorithms/models in iterations, preferably utilizing Python, Scikit-Learn, TensorFlow/Keras, and PyTorch. The candidate must be able to find useful data sources and automate the data collection procedure. They must also undertake statistical analysis and fine-tuning based on text outcomes. The ideal candidate will have knowledge of Python, R, SQL, and/or NoSQL databases, as well as Scala, Java, or C++.

Qualifications: 
A B.Sc/B.A/B.E/B.Tech/M.C.A - in computer science, engineering, mathematics, statistics, or a related discipline is required. A data science graduate will be given special consideration.
Should have 5-8 years of experience in the industry.

The candidate should have strong analytical skills as well as knowledge of mathematics and statistics.

For evaluating data, he or she will need analytical reasoning and problem-solving abilities.
As a senior data scientist, the person must be able to guide and direct a team of 3-5 data scientists while also contributing independently.

Undoubtedly, data scientists can work in any field given the requirement of their expertise in this modern technological world. If you are interested and are intrigued by the challenges of the dynamics of data and the rapid growth, Data scientist perhaps is your calling and should start honing your knowledge and skills now. 

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