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Acquiring the Best Data Science Talent for your Team in 2022/data-science-insights/acquiring-the-best-data-science-talent-for-your-team-in-2022

Acquiring the Best Data Science Talent for your Team in 2022

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Acquiring the Best Data Science Talent for your Team in 2022

Big data is ineffective without the expertise of data science professionals who can transform the data into actionable insights. In the modern world, numerous organizations are using the power of big data, and a data scientist knows how to churn out business-relevant insights from a vast pool of information.

The present digital world leaves tons and tons of data and contributes massive amounts of unsegregated information to organizations. An IBM report says that the poor quality data costs around USD 3.1 trillion annually in the US.

Since there is an upsurge in the amount of data that needs to be processed and analyzed, the role of a data scientist is significant in every organization.

Why would an organization need Data Science Talent?

Data scientists are the present-world superheroes who let the companies make prompt and relevant decisions in favor of the improved productivity of the organization. 

Here are the ways a data science talent can be helpful to organizations. 

  • Stimulating business decisions with action-specific data processing
  • Deciding and implementing actions based on the modern world trends to define the goals
  • Directing the staff to take ideal practices and emphasize issues that can drive more results
  • Testing and concluding the right business decisions
  • Understanding and refining the target audience
  • Sourcing the right talent that suits the organization requirements

 Role of Data Science Professionals in empowering organizations 

Data scientists are those who undergo intensive training in various technical and non-technical skills. The experience of data science professionals extends to a wide horizon like data mining, data visualization, data management, etc. 

Here are some ways in which data science can benefit organizations: 

  • Fraud detection and mitigation:

    Data scientists are usually trained to implement big data methodologies, statistics, networks, and other big data techniques to deploy predictive fraud detection models and utilize them to create timely responses. As per the report from ACFE, the average fraud can cost over USD 1.5 million to the organizations.

    Lebara, a prominent UK-based mobile network operator, could detect, identify, and effectively block the unlimited SIM cards used by hackers to initiate calls to their paid numbers. Similarly, Deutsche Bank utilized big data and Artificial Intelligence to facilitate KYC processes, prevention of credit card fraud, money laundering identification, etc. 

  • Delivering the accurate products

    Data Analysts help organizations to easily find how, when, and where they can sell their products and services in the best possible ways. They can deliver the right products at the perfect time, help businesses to develop new products, and build customer satisfaction.

    Amazon leverages about 90 warehouses, more than 50 cargo planes, and almost thousands of delivery trucks, with data science algorithms to plan and decide on the optimal logistical processes.

  • Personalized customer experiences

    Data science professionals are capable to help drive the sales and marketing teams with insightful data and helping them to deliver products or services based on the targeted customer preferences.

    Boots UK is a British Health & Beauty retailer, which uses tailored data science-driven techniques to extract customer insights and deliver customer-specific promotions.

How various Data Science Job Profiles benefit organizations

As per the U.S. Bureau of Labor Statistics, it is estimated that the number of data science jobs will improve by almost 28% through 2026. In every organization, various job profiles in data science contribute to the development of the organization in different ways as shown below. 

  • Data Engineer

    Data engineers can help organizations with data pipelines to collect the data, convert them into a useful form, create infrastructure to fetch the data and store them easily.

  • Data Analyst

    A Data Analyst assists the business structure analysis, through vigorous statistical analysis of business-specific information and contributing to the extension of the business.

  • Data Architect

    A Data Architect creates the design of an organizational database. They help in the protection, maintenance, centralization, and integration of the different data sources.

  • Statistician

    Statisticians are responsible for data analysis and visualization and help organizations with the application of statistical theories for data interpretation.

  • Data Scientist

    Data scientists use data visualization to extract meaningful insights, develop predictive models, and Machine learning algorithms to automate them, where organizations can solve everyday challenges and manage real-time projects.

  • Database Administrator

    Database administrators take care of the proper working of security concerns like backup and database recovery systems. They are responsible to make sure that the database is available to the users with high-end security.

  • Business Analyst

    A business analyst collects data about the organization's needs, client's needs, etc., and proposes the operational processes required to magnify the business results.

  • Data & Analytics Manager

    They are responsible to make effective strategies that help data accumulation. They take care of the data quality and integrity to help organizations use quality-centric data.

Must-have values for Data Science Professional

According to a Harvard Business Review, the companies that are in the top third of the industry they belong to, use data science-based decisions and are found to be 5% more productive, and about 6% more profitable compared to the competitors. Here are the values organizations should look for while hiring data science talent.

  1. Decision-making skills

    Being the strategic partner to any organization, a data scientist should be able to serve the organization's projects through communication and demonstration of value-oriented data.  With extensive tracking, measuring, recording, and implementation of data, they contribute to improving business outcomes.

  2. Directing actions based on trends

    With the clear examination and analysis of organizations' data, data scientists examine the data and should be able to formulate actions that can improve the organizations' performance, help with customer engagement and improve profitability.

  3. Communication capabilities to support the staff

    Data scientists should be capable of ensuring that the staff is well-versed with the analytics products. They must be able to prepare the staff to demonstrate the use of the system to drive action through effective insights extraction.

  4. Business acumen and logic

    Data scientists should be able to interact with the existing analysis system and question the existing business processes to develop the analytic algorithms that can improve the value derived from the business-related data.

  5. Well versed in technical skills

    The following skills are highly in demand for the organizations that hire data science professionals to make crucial business decisions.
    • Probability & Statistics
    • Mathematical Skills
    • Programming knowledge- Hadoop, R, Scala, C, Java, Python
    • Database Management
    • Data Wrangling
    • Data Visualization
    • Machine Learning & Deep Learning skills
    • Cloud computing


  6. Ability to Measure the decisions and test them

    Data scientists should be able to know how the business decisions affect the organization and should be able to measure the key features related to the significant changes and test them.

  7. Ability to generate customer insights

    Companies will have customer surveys, Google analytics, and other measures to source the customer data. Data scientists must ensure that the data is segregated and useful information is used to generate insights that can help organizations to generate more leads.

Conclusion

Data science is an asset to every organization and triggers decision-making, market trend analysis, and profit maximization. Data science certifications can help you be equipped with the essential data science skills and turn out to be an asset to organizations through the development of all the above-mentioned Data science qualifications.

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