The area of machine learning, which is quickly expanding, uses statistical methods and data analysis to teach computers how to learn and make predictions or judgements without being explicitly programmed.
There is a rising need for employees with entry-level expertise in machine learning as businesses and industries increasingly understand its usefulness. Here are five entry-level positions in machine learning that present fascinating chances for those looking to launch their careers in this area.
Machine learning engineer
- The role: Machine learning engineers develop, deploy and maintain machine learning models and systems.
- Required skills: Strong programming skills (Python, R, etc.), knowledge of machine learning algorithms and frameworks, data preprocessing, model evaluation, and deployment.
- Degree: Bachelor’s or higher in computer science, data science or a related field.
- Job opportunities: Machine learning engineers can work in industries such as technology, finance, healthcare and e-commerce. Opportunities are available in both established companies and startups.
How much math do you need to become a Machine Learning engineer?
This is the most common question people ask.
A few years ago, understanding low-level math details was crucial. Even today, math is essential if you want to become a researcher focusing on improving and… pic.twitter.com/5rrYQmUkPz
— Santiago (@svpino) June 26, 2023
Data scientist
- The role: Data scientists analyze and interpret complex data sets to derive insights and build predictive models.
- Required skills: Proficiency in programming (Python, R, etc.), statistical analysis, data visualization, machine learning algorithms and data manipulation.
- Degree: Bachelor’s or higher in data science, computer science, statistics or a related field.
- Job opportunities: Data scientists are in demand across various industries, including finance, healthcare, marketing and technology. Companies ranging from startups to large enterprises actively seek data science talent.
Related: 5 high-paying careers in data science
AI researcher
- The role: AI researchers focus on advancing the field of artificial intelligence through research and development.
- Required skills: Strong knowledge of machine learning algorithms, deep learning frameworks — e.g., TensorFlow, PyTorch — programming skills, data analysis and problem-solving abilities.
- Degree: Master’s or Ph.D. in computer science, artificial intelligence or a related field.
- Job opportunities: AI researchers can work in academia or research institutions or join research teams within technology companies. Positions are available in both public and private sectors.
Machine learning consultant
- The role: Machine learning consultants provide expertise and guidance to businesses in implementing machine learning solutions.
- Required skills: Solid understanding of machine learning concepts, data analysis, project management, communication skills and ability to translate business requirements into technical solutions.
- Degree: Bachelor’s or higher in computer science, data science, business analytics or a related field.
- Job opportunities: Machine learning consultants can work in consulting firms, technology companies or as independent consultants. Opportunities exist across various industries seeking to adopt machine learning.
Related: 11 tech jobs that do not require coding skills
Data engineer
- The role: Data engineers design and maintain data infrastructure, ensuring efficient storage, processing and retrieval of large data sets.
- Required skills: Proficiency in programming (Python, SQL, etc.), database systems, data pipelines, cloud platforms — e.g., AWS, Azure, GCP — and data warehousing.
- Degree: Bachelor’s or higher in computer science, software engineering or a related field.
- Job opportunities: Data engineers are in high demand across industries, particularly in technology, finance and healthcare. Both established companies and startups require data engineering expertise to handle large volumes of data.
Please note that the required skills, degrees and job opportunities mentioned above are general guidelines and can vary based on specific companies, roles and regions. It’s advisable to research and tailor your skills and qualifications to the specific job requirements when pursuing a career in machine learning.