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Predictive Analytics Machine Learning Software Jobs

Manulife

Director, AI

Boston, MA · On-site

... software engineering, and cloud technologies . The candidate should have strong hands-on experience ... This includes experience across both traditional predictive analytics, machine learning , and MLOps ...

Apple

Machine Learning Software Engineer

Sunnyvale, CA · On-site

$181.10K - $318.40K/yr

S and 7+ years of experience in software engineering, computer vision, machine learning or related fields. Strong experience in Python. Working experience in C++ or Swift. Foundational understanding ...

Peraton

Cyber Systems Engineering Manager

Lanham, MD · On-site

Oversee predictive analytics, machine learning, and forensic analysis activities used to identify fraudulent and anomalous behavior. * Support the development and implementation of fraud indicators ...

Apple

Machine Learning Software Engineer

Sunnyvale, CA · On-site

S and 7+ years of experience in software engineering, computer vision, machine learning or related fields.Strong experience in Python.Working experience in C++ or Swift.Foundational understanding of ...

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Predictive Analytics Machine Learning Software information

What are the key skills and qualifications needed to thrive as a Predictive Analytics Machine Learning Software Engineer, and why are they important?

To thrive in predictive analytics and machine learning software roles, you need a strong background in statistics, programming (often Python or R), and machine learning concepts, typically supported by a relevant degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, and cloud platforms (e.g., AWS, Azure) as well as certifications in data science or ML are highly valued. Problem-solving, analytical thinking, and effective communication skills help professionals interpret data and collaborate across teams. These skills and tools are crucial for building accurate models, deriving actionable insights, and driving business value from data.

What are some common challenges faced by professionals working in predictive analytics machine learning software roles?

Professionals in predictive analytics machine learning software roles often encounter challenges such as handling large and complex datasets, ensuring data quality, and selecting appropriate algorithms for specific business problems. Additionally, they must effectively communicate technical findings to non-technical stakeholders and work collaboratively with cross-functional teams, including data engineers and business analysts. Staying updated with evolving technologies and best practices is also crucial for long-term success in this fast-paced field.

What is predictive analytics machine learning software?

Predictive analytics machine learning software refers to specialized tools and platforms that use statistical algorithms and machine learning techniques to analyze historical data and make predictions about future outcomes. These software solutions help organizations identify patterns, trends, and relationships within their data, allowing them to make data-driven decisions and forecasts. They are commonly used in fields such as finance, healthcare, marketing, and supply chain management to optimize processes and improve business performance.
Data Analyst Machine Learning - Hybrid

Data Analyst Machine Learning - Hybrid

Software Technology Inc

Manhattan, NY • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Data Scientist

Designing and maintaining data systems and databases; this includes fixing coding errors and other data-related problems. Mining data from primary and secondary sources, then reorganizing said data in a format that can be easily read by either human or machine. Using statistical tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts.

Required Skills/Experience (Skills that the successful candidate(s) must have)
  • Bachelor's degree in data science, data analytics, or a related field.
  • Proficiency in programming languages: SQL, Python and PySpark.
  • Minimum 3 years of experience with data visualization tools such as Power BI, Dax Queries, and best practices.
  • Experience with GenAI and large language models.
  • Must know how to analyze the root cause of dashboard errors.
  • Have experience in ML Ops and have strong coding background.
  • Have experience with Natural Language Processing (NLP).
  • Expertise in data mining and machine learning.
  • Knowledge or experience with A/B Testing.
  • Working knowledge of designing, training, and implementing machine learning models.
  • Familiarity with cloud-based infrastructure.
  • 7 or more years of experience in data science and machine learning.
Additional Skills (Skills that are a plus, but not required)
  • Master’s degree or Ph.D. in a quantitative field, such as statistics, computer science, mathematics, or engineering.
  • Azure Databrick Data Engineer Certification is a plus.
  • Experience with big data analytics technologies such as Spark and Hadoop.
Responsibilities
  • Collaborate with business stakeholders to understand their requirements and translate them into technical specifications.
  • Communicate insights and findings to business stakeholders.
  • Build, deploy, and maintain data management systems and back-end data infrastructure for our machine learning pipeline.
  • Build dashboards and analyze the root cause of dashboard malfunctions.
  • Perform data mining, exploration, and analysis.
  • Create data visualizations, reports, dashboards, and data audits.
  • Design, train, and implement machine learning algorithms.
  • Leverage predictive models to optimize customer experiences.

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