Associate Software Engineer - Data Scientist

What you will do

At Johnson Controls, we’re shaping the future to create a world that’s safe, comfortable, and sustainable. Our global team creates innovative, integrated solutions to make cities more connected and buildings more intelligent. We are passionate about improving the way the world lives, works and plays. The future requires bold ideas, an entrepreneurial mindset, and collaboration across boundaries.

How you will do it

• Facilitate to manage development and delivery of technical communications within the assigned knowledge management system.

• Utilize the accumulation of information by external and internal end-user communities as well as forums.

• Pair with Subject Matter Expert to create and evaluate data driven solutions.

• Track success of data driven solutions using attribution methodologies.

What we look for

• Bachelor's or master’s degree in computer science, Statistics, Mathematics, or related field.

• 3-5 years of experience in a data science or analytics role, with a proven track record of delivering impactful insights, products, and solutions.

• Proficiency in programming languages such as Python or R, and experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn).

• Strong understanding of machine learning techniques and algorithms, such as regression, classification, clustering, and deep learning.

• Experience with data visualization tools (e.g., matplotlib, seaborn, Tableau) and SQL databases.

• Excellent problem-solving skills and attention to detail, with the ability to work independently and collaboratively in a fast-paced environment.

• Strong communication and interpersonal skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences.

• Experience with distributed data/computing tools: Snowflake, Spark, MySQL, etc.

• Experience in Azure and Azure ML is a must

• Experience with data engineering tasks such as data pipeline development, data warehousing, or data integration.

• Proficiency in version control systems (e.g., Git) and collaboration tools (e.g., JIRA, Confluence).

• Understanding of ethical considerations and best practices in data science, including privacy, bias, and fairness.

• Demonstrated experience working with multiple specialties in a "one-team" environment.

• Experience across a variety of technical disciplines.

• Excellent oral, written, and interpersonal communication skills.

 Preferred Qualifications:

• Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP).

• Knowledge of natural language processing (NLP) techniques and tools.

• Experience with A/B testing methodologies and experimental design.

• Publications or presentations in relevant conferences or journals.

• Certifications in data science or related fields (e.g., AWS Certified Machine Learning Specialty, Google Professional Data Engineer).