Data Scientist

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 Scientist with Advanced Analytics skills, you will leverage deep data and analytics expertise with strong business acumen to address business challenges. You will utilize data preparation, analysis, and predictive modeling to forecast trends and suggest optimizations for improved business outcomes. Your primary responsibilities will include:

• Analyze and Interpret Data: Utilize mathematical optimization, discrete-event simulation, and predictive analytics to extract insights from diverse data types and structures, ensuring data-driven decision-making and business optimization.
• Develop Predictive Models: Apply proficiency in programming languages, particularly Python, to design and implement predictive models that forecast trends and suggest optimizations for improved business outcomes.
• Manipulate and Visualize Data: Employ expertise in data manipulation using tools such as Pandas, NumPy, and Dask, and data visualization with Matplotlib, Seaborn, and Plotly to effectively communicate insights to stakeholders.
• Manage and Analyze Databases: Utilize experience in managing databases like SQL, MongoDB, Cassandra, PostgreSQL, and MySQL to store, retrieve, and analyze large datasets.
• Implement Optimization Solutions: Apply knowledge of optimization tools like IBM CPLEX and Gurobi to develop and implement optimization solutions that drive business value.

In line with applicable pay transparency requirements, we are sharing the annual base pay range (gross per year). These amounts are based on a full-time schedule over a full calendar year.

The final offer may vary depending on your skills, qualifications, and experience, as permitted under applicable local law.

At IBM, we offer a comprehensive benefits package, which includes

• Opportunities for personal and career development
• Additional paid time off
• Comprehensive health coverage, including critical illness, life, and disability insurance, plus access to a medical center
• 100% paid sick leave for up to 60 days
• MultiSport card
• Exclusive IBM discounts on sports, travel, cultural activities, shopping, health, beauty, and dining

If you are successfully selected for offer, we will share the full details of the compensation package and benefits with the offer letter.

Preferred Education

Bachelor's Degree

Required Technical And Professional Expertise

• Data Analysis and Modeling: Exposure to data preparation, analysis, and predictive modeling to forecast trends and suggest optimizations for improved business outcomes.
• Programming Languages: Exposure to programming languages, particularly Python, and development environments like PyCharm, VS Code, and Jupyter Notebooks.
• Data Manipulation and Visualization: Experience working with data manipulation tools such as Pandas, NumPy, and Dask, and data visualization with Matplotlib, Seaborn, and Plotly.
• Database Management: Exposure to managing databases like SQL, MongoDB, Cassandra, PostgreSQL, and MySQL to store, retrieve, and analyze large datasets.
• Optimization Tools: Experience working with optimization tools like IBM CPLEX and Gurobi to develop and implement optimization solutions.

Preferred Technical And Professional Experience

• Machine Learning Knowledge: Exposure to machine learning concepts and techniques, including statistical modeling and custom models in applications like supply chain management, pricing, risk assessment, and fraud detection.
• Statistical Analysis Skills: Familiarity with statistical analysis tools like SPSS, SAS, and R, in addition to Python, to analyze and interpret complex data sets.
• Version Control Systems: Experience working with version control systems such as Git, GitHub, and GitLab, and continuous integration and deployment (CI/CD) tools like Docker, Podman, and Jenkins.