Join the world of data science with these lucrative job roles!

The emergence of artificial intelligence boosted the adoption of data science. This technology has become an invaluable asset for industries across the globe. With massive amounts of data being produced daily, customers expect that the companies manage this data carefully; hence there has been an increase in the employment for data science professionals. Businesses are benefitting from this data by drawing meaningful insights to make more data-driven decisions.

Here are the top 10 data science jobs for tech aspirants that are trending in 2021.

• Analytics Translator: Becoming a good analytics translator requires technical knowledge and a certain business understanding. An analytics translator can adequately prioritize machine learning initiatives according to the business objectives. In this job role, the candidates are required to build relations with people from other businesses and manage relevant projects.

• Data Architect: Data architects are responsible for articulating new data collections, ensure accurate data quality, eliminate data redundancy, and work on creating the best architecture design for business intelligence and analytics workflows.

• Data Scientist: Data scientists play a vital role in business setups. They understand the market obstacles and provide the best solutions using data analysis and processing. The candidates are required to possess skills in computer science, statistics, and mathematics, as they analyze, process, and model data to attain business objectives.

• Data Engineer: Data engineers work in a variety of settings to build systems that collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret their next course of action to reach organizational goals. They create data pipelines and cloud data integrations, solve complex data problems and address data plumbing issues.

• Data Analyst: The primary responsibility of a data analyst is to understand the needs of investment researchers, analyze various data resources for any potential inconsistencies, execute data analytics projects and assignments, and create reports for data collection.

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• Software Engineer-Data Platform: The candidates have to work on building resilient and thoroughly tested distributed systems. They work hand-in-hand with machine learning engineers to understand the inputs and outputs provided by the models. Software engineers should have a deeper understanding of the different programming languages and robust software developing applications.

• Machine Learning Engineer: Machine learning engineers need to possess detailed knowledge about data science and software engineering. They have to master model deployment, ensure metric monitoring, solve pipeline integration, and ensure scalability and flexibility of the deployment environment.

• Python Backend Developer: The developers work on designing software solutions and ensure that the provided solutions are within the constraints of architectural guidelines. They also ensure that the automation guidelines are accurately followed and guide the scrum team members on design topics. They also collaborate with various teams and analyze their software requirements.

• Business Intelligence Analyst: Business intelligence analysts transform data into insights to boost business profits. With the help of data analytics, visualization, and processing, BI analysts identify the market trends to help managers and business leaders understand potential business threats and boost profits.

• Statistician: Statisticians apply statistical methods and models to real-world problems. They gather and interpret data to aid businesses in their decision-making processes. They also design processes for data collection and communicate with stakeholders to advise on organizational and business strategies.