From personalized recommendations on streaming services to predictive text on our smartphones, data science is behind the scenes.
This rapidly growing field encompasses various activities, such as data collection, processing, sophisticated modeling, and insightful analysis.
Read on to discover the different data science roles and responsibilities and see if any spark your interest and could be a potential career path for you.
When people think of data science professionals, they likely picture data scientists. However, that is just one role within the broader field of data science, which encompasses various roles essential for processing, analyzing, and deriving insights from data. For example, data analytics differs from data science because it’s a more specialized area within data science.
Below, we’ll explore several of them to provide you with a comprehensive view of the field.
A data scientist leverages advanced statistical methods, machine learning algorithms, and technology to provide actionable intelligence that drives strategic business decisions. Key responsibilities include:
To excel as a data scientist, professionals need the following skills:
To become a data scientist, you typically need a bachelor’s or master’s degree in data science, computer science, statistics, mathematics, or a related field. Moreover, certifications such as Certified Analytics Professional (CAP), Open Certified Data Scientist (Open CDS), Microsoft Certified Azure Data Scientist Associate, or other relevant data science and machine learning options can also be beneficial.
Data analysts examine datasets to identify trends and make informed business decisions. They play a significant role in transforming raw data into meaningful information. Some of their key responsibilities include:
To work as a data analyst, you need the following skills:
A bachelor’s degree in mathematics, statistics, computer science, information management, or a related field is typically required. A master’s degree is beneficial for advanced roles, whereas certification is not mandatory but can help further enhance career prospects.
A data engineer designs, constructs, installs, and maintains large-scale processing systems and databases. Some of the top responsibilities for professionals in this role include:
To succeed as a data engineer, one needs to have a specific skill set, which includes:
For this role, you need a bachelor’s degree in computer science, information technology, engineering, or a related field. Advanced degrees, such as a master’s in data engineering or a related discipline, can further enhance job prospects and expertise. Additionally, coursework in database management, data warehousing, and big data technologies is highly beneficial.
A data architect creates blueprints for data management systems to integrate, centralize, protect, and maintain data sources. Their day-to-day duties include:
Data architects need the following skills to fulfill their duties:
To become a data architect, you need a bachelor’s degree in computer science, information technology, or a related field. Additionally, advanced degrees, such as a master’s in data architecture or information systems, can significantly enhance career prospects and expertise.
A machine learning engineer designs and implements machine learning models and algorithms that leverage large data sets. Their key responsibilities encompass the following:
When it comes to their skillset, this role requires:
A bachelor’s degree in computer science, statistics, mathematics, or a related field is typically required for this role. Advanced degrees, such as a master’s or Ph.D. in machine learning or artificial intelligence, as well as relevant coursework in algorithms, data structures, statistics, and machine learning, can significantly enhance career prospects and provide deeper expertise.
These professionals help intertwine IT and business by using data analytics in order to assess processes, determine requirements, and deliver data-driven recommendations. Some of their main duties include:
A bachelor’s degree in business administration, information systems, or a related field is required for entry-level positions in this field. Moreover, while not mandatory, certifications such as Certified Business Analysis Professional (CBAP) or PMI Professional in Business Analysis (PMI-PBA) can enhance career prospects and credibility in the field.
A product manager oversees the development and delivery of products, ensuring they meet customer needs and business goals. Other responsibilities include:
A product manager needs to master the following skills:
Typically, the educational requirements include a bachelor’s degree in business administration, marketing, or a similar field. Advanced degrees or an MBA can be advantageous. Additionally, certifications like Certified Scrum Product Owner (CSPO) or Product Management Certification by Pragmatic Institute can further validate skills and knowledge in the field.
The exact path to becoming a data scientist can vary depending on the specific role you aim for within the data science domain. You might have to adjust your educational and professional journey according to the requirements and expectations of your targeted position.
Most data science positions typically require a bachelor’s degree in data science, computer science, statistics, mathematics, or a related field. This foundational education equips you with the essential skills and knowledge. After graduation, seeking entry-level positions such as a data analyst or junior data scientist is beneficial. These roles offer practical experience and a deeper understanding of real-world data challenges, which are invaluable for your professional growth.
While not always necessary, a master’s degree in data science, machine learning, artificial intelligence, or a related discipline can enhance your expertise and job prospects. Similarly, certifications can validate your skills and knowledge, making you more competitive in the job market.
Data science is a lucrative career. The median annual wage for data scientists is $108,020. Salaries in this field can vary widely based on experience, location, and industry. The lowest 10 percent of data scientists earn around $61,070, while the highest 10 percent can make over $184,090. This wide range reflects the diverse opportunities and career paths in data science.
Each role within data science plays a crucial part in transforming data into actionable insights. If you’re considering a career in this exciting field, UND offers a range of undergraduate and graduate degree options tailored to equip you with the necessary skills and knowledge. As a founding member of the Midwest Big Data Innovation Hub, UND also provides fantastic networking opportunities through collaborative projects and events. So, join us at UND and be part of a community shaping the future of data science. Ready to turn data into discovery? Your journey starts here.
Yes, data scientists are in high demand, with a 35% projected job growth from 2022 to 2032, much faster than the average for all occupations.
A good data scientist possesses strong analytical skills, proficiency in programming languages like Python or R, expertise in statistical methods, and the ability to communicate insights effectively to stakeholders.
Data scientists typically collaborate with cross-functional teams, including data analysts, data engineers, machine learning engineers, product managers, and business stakeholders.
Yes, data scientists frequently code, primarily using languages such as Python, R, and SQL to manipulate data, build models, and perform analyses.
Earn your B.S. Data Science degree online or on-campus at UND – an accredited and affordable data science school in the Midwest.
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