Data Engineer-Machine Learning - 2

IBM Computing; San Francisco (CA); Remote; USD 120,000 - 190,000; Full time

Job summary

IBM Consulting is seeking a Data Engineer with expertise in Machine Learning to design and deploy ML solutions that address real business challenges. You will work across teams to translate data into actionable insights and drive informed decisions in client engagements.

The role emphasizes feature engineering, model evaluation, and clear communication of results to stakeholders, with the flexibility to work remotely within the United States.

Qualifications

• Expertise applying ML to business problems.
• Ability to interpret and analyze statistical data for decisions.
• Experience evaluating ML algorithms with relevant metrics.
• Clear communication of ML results to stakeholders.
• Collaborate to integrate ML insights into business decisions.

Responsibilities

• Develop ML models to address business challenges.
• Evaluate model performance using relevant metrics.
• Interpret and communicate insights to stakeholders.
• Collaborate with teams to integrate ML into decision-making.

Skills

Machine Learning

Statistical analysis

Algorithm evaluation

Communication

Strategic decision-making

Tools

TensorFlow

PyTorch

Scikit-Learn

Job description

Introduction

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your role and responsibilities

As a Data Engineer with expertise in Machine Learning, you will apply Machine Learning concepts and techniques to address business challenges. You will leverage your skills to drive informed decision-making in the organization.

Your primary responsibilities will include:

• Develop Machine Learning Solutions: Design and implement Machine Learning models to solve complex business problems, selecting relevant features and algorithms to achieve desired outcomes.
• Evaluate Algorithm Performance: Assess the effectiveness of Machine Learning algorithms using relevant metrics, identifying areas for improvement and optimizing model performance.
• Interpret Statistical Data: Analyze and interpret complex statistical data to inform business decisions, communicating insights and recommendations to stakeholders.
• Communicate Results: Clearly articulate the results of Machine Learning initiatives, providing actionable insights and recommendations to drive business outcomes.
• Drive Informed Decision-Making: Collaborate with stakeholders to integrate Machine Learning insights into business decision-making processes, driving informed strategic choices.

This role can be performed from anywhere in the United States of America.

Required technical and professional expertise

• Deep Expertise in Machine Learning: Proven ability to apply Machine Learning concepts and techniques to address complex business challenges, leveraging expertise in algorithm selection, feature engineering, and model optimization.
• Experience with Statistical Data Analysis: Skilled in interpreting and analyzing complex statistical data to inform business decisions, with the ability to identify relevant trends and patterns.
• Algorithm Evaluation and Optimization: Experienced in evaluating the performance of Machine Learning algorithms using relevant metrics, with a strong understanding of optimization techniques to improve model performance.
• Effective Communication of Results: Adept at clearly articulating the results of Machine Learning initiatives, providing actionable insights and recommendations to drive business outcomes.
• Strategic Decision-Making: Proven ability to collaborate with stakeholders to integrate Machine Learning insights into business decision-making processes, driving informed strategic choices.

Preferred technical and professional experience

• Advanced Statistical Modeling: Experience with developing and applying advanced statistical models to drive business insights, leveraging techniques such as regression analysis, time series forecasting, and hypothesis testing.
• Machine Learning Frameworks: Familiarity with popular Machine Learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn, with the ability to design and implement scalable Machine Learning solutions.
• Data Visualization Tools: Exposure to data visualization tools such as Tableau, Power BI, or D3.js, with the ability to effectively communicate complex data insights to stakeholders.

IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.