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Data Scientist Machine Learning Jobs in Alabama (NOW HIRING)

4pconsultinginc

Data Scientist III (IT)

Birmingham, AL · On-site

Data Scientist III (IT) Location: Birmingham, AL Duration: 1 Year Client: Alabama Power Job Summary ... This role requires strong expertise in statistics, machine learning, and programming , with the ...

PNC Bank

Data Scientist

Birmingham, AL

A Data Scientist will bring forth a strong focus on building intelligent agents, automation, and ... Develops algorithms using advanced mathematical and statistical techniques like machine learning to ...

New

UAB NOVA RENT

DATA SCIENTIST LEAD

Birmingham, AL · On-site

$104K - $169K/yr

Typically includes creating various machine learning-based tools or processes within the unit, such ... Data scientist lead for the Sight Outcomes Research Collaborative (SOURCE), a consortium of ...

Apex Systems

Data Scientist

Birmingham, AL · On-site

Job#: 3033520 Job Title Data Scientist - Nuclear Operations Job Summary The Data Scientist develops ... Develop, validate, and maintain statistical, machine learning, and time-series models for use cases ...

Genuine Parts Company

Data Scientist

Birmingham, AL · On-site

SUMMARY Under limited supervision, the Data Scientist works closely with business stakeholders to ... Must have a passion for machine-learning and research. This position will be tasked with helping ...

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$34K

$111.2K

$178.1K

How much do data scientist machine learning jobs pay per year?

As of Jun 11, 2026, the average yearly pay for data scientist machine learning in Alabama is $111,249.00, according to ZipRecruiter salary data. Most workers in this role earn between $89,300.00 and $123,300.00 per year, depending on experience, location, and employer.

What is a Data Scientist Machine Learning job?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the Data Scientist Machine Learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

Is ML a high paying job?

Data Scientist Machine Learning roles are generally well-paid due to the specialized skills required, such as programming in Python or R and knowledge of algorithms. Salaries vary by experience, location, and industry, but they tend to be higher than average for tech roles, reflecting the demand for expertise in machine learning and data analysis.

Is 40 too late for data science?

Data scientists can enter the field at any age, including 40 or older, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning tools. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

Which 5 jobs will survive AI?

Data Scientist Machine Learning roles are likely to persist as they require advanced analytical skills, domain expertise, and the ability to interpret complex models. Jobs that involve creative thinking, emotional intelligence, and tasks requiring human judgment—such as healthcare professionals, educators, and skilled trades—are also expected to remain resilient despite AI advancements.

What are the typical day-to-day responsibilities of a Data Scientist Machine Learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

Do data scientists do machine learning?

Yes, data scientists often use machine learning techniques to analyze data, build predictive models, and extract insights. Proficiency in programming languages like Python or R and understanding of algorithms are essential skills for applying machine learning in their work.
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