Why are data science, analytics, and market research such a competitive, hard to get in the field, when data Jobs should be blooming?

The upgrading technology requires an improved, well-equipped and up-to-date IT manpower who can manage different forms of data for the business.

Despite the rise in IT experts and technicians, it’s getting tougher to get into the data job mainly because organizations focus on hiring the most learned and capable professional.

What is Data Science?

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured.

Less than 0.5% of all data we create is ever analyzed and used.

Why do you need a Data Scientist?

A data scientist can be important for the organization for many reasons.

a. Mitigate risk and fraud

Data scientists have an eye for identifying the right data. They create statistical methodologies for predictive fraud propensity models and use the methodologies to create an alert when unusual data is recognized.

b. Delivering relevant products

Data Science helps organizations to locate the best market for their products. This lessens the chance of glut in the market and promotes the production and marketing of the right products at the right time.

c. Personalized customer experiences

Understanding data helps to understand personal goals or consumers. Businesses can ascertain what their customers need, which helps to personalize the services and provide the right service to the right consumer.

Are Data science, analytics, and market research the same?

Data science pertains to obtaining information and insights from data in various forms, both structured and unstructured.

Analytics refers to the systematic computational analysis of data or statistics. It helps to stud past historical data to research potential trends, to analyze the effects of certain decisions or events, or to evaluate the performance.

Market Research refers to the action or activity of gathering information about consumers' needs and preferences. Market Research is all about researching market trends, customer needs, business products, and target audience to improve an organization’s marketing and sales campaign.

There are several ways to categorize the various market research methods. The vast majority of techniques fit into one of six categories:

1. Secondary research
2. Surveys
3. Focus groups
4. Interviews
5. Observation
6. Experiments/field trials

All of these correlate to each other and are codependent in many cases. Data science is essential to carry out analysis of data. Market research isn’t possible without both data science and analytics. A data scientist can offer insights that apply for both analytical field and market research techniques.

When data jobs should be blooming, why it is hard to get in the field?

STEM (Science, technology, engineering, and mathematics) is the most sought-after academics by any college student. Hundreds and thousands of people graduate with the same degree as you, hence increasing the completion. The thing about the Data Science field is that there is always someone better than you. The other person may have more exact experience than you or have a higher degree or went to a great school.

• There are a lot of people that study STEM. On top of this, we have a lot of H1B and student visas who come here to study in the U.S. and they are all looking for jobs. Around 500k people every year!
• This is not a niche industry where the employer can’t find candidates.
• An average job posting gets 100s of applications. Probably around 600.

A niche profession always has a better chance of landing the job, however, jobs like data scientists, electrical engineers, programmers, and data analysts are too generic. There are thousands of other people who can do the same job. What you are facing is the competition from those A level students. Smart people are in fact, dime a dozen!

Ultimately, unless you can demonstrate that you are the best of the best, you will not get a job as the data scientist.

Importance of data scientist and analyst in an organization

A data scientist is someone who can predict the future based on past patterns whereas a data analyst is someone who merely curates meaningful insights from data.

Importance of hiring a data scientist

The data scientist can help achieve major organizational goals.

i. Empowering management to make better decisions

The availability of the right data helps organizations or the management to make better decisions. The statistical method of refining and analyzing data provides accurate data to initiate the right marketing, sales, or any other organizational plan.

ii. Actionable Plans

Data Scientist examines and explores the organization and competitor’s data that helps to recommend certain actions that will help improve the organization’s performance.

iii. Promote Best Organizational Practices

Data scientists ensure that the organization is familiar and well-versed with the business analytics product.

iv. Identifying Opportunities

Data Scientists question the existing processes and assumptions and find out faults that need to be mitigated.

v. Test Decisions

Data Science helps to measure the propensity of the management’s decision using the data in hand.

vi. Identification of Target Audiences

The availability of data and analytics helps to understand the right market, right marketing plan, and the right audience.

vii. Right Talent for the Organization

The use of data science isn’t only limited to marketing, sales, or operations. It can help to locate and hire the right talent for the organization.

Importance of hiring an analyst

Some of the reasons why an organization should hire an analyst are as follows:

• Predict customer trends and behaviors
• Analyze, interpret and deliver data in meaningful ways
• Increase business productivity
• Drive effective decision-making
• Understand business direction and objectives
• Explore the meaning behind the numbers and figures in data
• Analyze the causes of certain events based on data findings
• Present technical insights using easy-to-understand language
• Contribute to business decision-making by offering informed opinions

Is work done by Data Scientist and Data Manager the same?

Not really. Data Scientist specializes in extracting information and insight from data for different purposes, whereas, data management refer to the overall management of data and professional to achieve certain organizational goal.

Data management is described as,

The coordination of people, processes, and data flows in order to achieve some set goals-which should include or result in deriving value from data.

Data management activities range from the technical such as data engineering to the non-technical such as data governance. It basically covers:

• Architecture & Modeling
• Storage & Operations
• Security
• Master data, Reference data, Document, Content & Metadata management
• Integration & Interoperability
• Warehousing & Business Intelligence
• Quality
• Governance

The Data Manager is concerned with the entire enterprise, department, and domain data but a specific dataset. They should maintain the integrity of the data through its entire lifecycle and ensures that it can be efficiently accessed by those who need to harness it.

Is data science in high demand?

The demand for data science skills is growing exponentially thanks to the exponential growth in the use of Data Science and A.I.

Indeed, one of the top job sites showed a 29% increase in demand for data scientists year over year and a 344% increase since 2013

Although the demand I high, searches by job seekers skilled in data science grew at a slower pace (14%), suggesting a gap between supply and demand.

Searchable Design a premier IT Company in Des Moines. We employ highly skilled and experienced Data Scientists to provide the best data science service in Des Moines.