Data Scientist – Mid Level

Moffatt & Nichol specializes in large complex waterfront infrastructure projects and is recognized as one of the worldwide leaders in this field. We are actively looking for a Data Scientist to join our Costa Mesa, CA office. As a successful Data Scientist, you will have 4 to 6 years of hands-on experience to perform exploratory data analysis and develop machine-learning models that drive data-informed decisions. This role requires strong analytical thinking, solid Machine Learning (ML) fundamentals, and the ability to translate business or operational problems into data science solutions.

We are seeking a curious, self-driven professional who is motivated by building solutions that deliver meaningful, real-world impact. You will join a collaborative, high-energy team that values learning, continuous improvement, and thoughtful problem-solving. We value individuals with a growth mindset, people who are comfortable navigating ambiguity, do not expect to have all the answers on day one, and genuinely enjoy learning and solving problems together.

In this role, you will operate within a rapidly evolving AI/ML (artificial intelligence/machine learning) landscape, gaining hands-on exposure to emerging tools, technologies, and best practices. You will be part of a supportive, forward-thinking team that shares ideas openly, challenges each other constructively, and cares deeply about building solutions that make a real difference.

About Moffatt & Nichol: 

Moffatt & Nichol is a leading U.S.-based global infrastructure advisor specializing in the planning and design of facilities that shape and serve our coastlines, harbors and rivers, as well as an innovator in transportation. For the 4th year in a row, Moffatt & Nichol is Ranked #1 in Engineering News-Record for Marine & Port Facilities in the U.S. Additionally, our firm consistently ranks in the Top 100 Pure Designers in the US and the Top 50 Designers in International Markets. 

Moffatt & Nichol's professional staff includes engineers, planners, scientists and architects who serve our global client base from offices in Europe, North America, Latin America, and the Pacific Rim. The firm provides clients worldwide with customized service and a level of excellence that have become the firm’s hallmark in several primary practice areas – ports and harbors; coastal, environmental and water resources; urban waterfronts and marinas; transportation, bridges and rail; inspection and rehabilitation; and energy. 

Duties and responsibilities:

Reasonable accommodations may be made to enable individuals with disabilities to perform these essential functions.

• Perform exploratory data analysis (EDA) to uncover patterns, anomalies, and actionable insights
• Design, develop, and evaluate machine-learning models (e.g., regression, classification, clustering, time series)
• Conduct feature engineering, model selection, and hyperparameter tuning
• Validate models using appropriate metrics and ensure robustness and interpretability
• Translate business problems into data science workflows and solutions
• Communicate findings through clear visualizations, reports, and presentations
• Collaborate with data engineers, software engineers, and domain experts to develop models
• Contribute to best practices in coding, experimentation, and documentation

Other duties:

Please note this job posting is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice.

Qualifications:

• 4 to 6 years of professional experience as a Data Scientist, Machine Learning Engineer or in a closely related role; required
• Master’s or Ph.D. degree in Data Science, Computer Science, Statistics, Engineering, or a related field; required
• Strong proficiency in Python (e.g., pandas, NumPy, scikit-learn, TensorFlow, Keras matplotlib/seaborn); required
• Solid understanding of statistics, probability, and machine-learning algorithms; required
• Experience performing structured EDA on real-world, messy datasets; required
• Knowledge of ML lifecycle tools (e.g., MLflow, Airflow, Docker); required
• Experience working with SQL and relational databases; required
• Ability to explain complex analytical results in a clear, business-focused manner; required 
• Experience with model deployment or production ML workflows; desired
• Familiarity with cloud platforms (Azure or AWS); desired
• Ex