RRemoteville

How Remoteville checks and expires listings

Brown and Caldwell logoBrown and Caldwell

Entry Level Data Scientist

Skills
Business RequirementsData AnalyticsData QualityData ScienceDatasetsExploratory Data AnalysisModel Selection
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • Bachelor’s, Master’s, or Ph.D. in Civil/Environmental Engineering, Environmental Science, or related field with focus on water resources, water treatment, and/or wastewater treatment
  • Bachelor’s, Master's, or Ph.D. in Computer Science, Data Science, Engineering, or related field with focus on machine learning, artificial intelligence, or data science coursework and/or research
  • 2+ years experience in developing and deploying machine learning models and data-driven solutions
  • Advanced knowledge of statistics, data preprocessing, exploratory data analysis, feature engineering, and model selection
  • Strong programming skills in Python and R and proficiency in relevant libraries and frameworks like TensorFlow, MLFlow, PyTorch, scikit-learn, DARTS, RLLib
  • Knowledge of software engineering principles, version control, and writing clean, maintainable, and scalable code with CI/CD experience
  • Experience with large datasets, databases, and data integration from various sources
  • Experience optimizing and tuning ML algorithms with standard search methods and advanced automatic ML tuning methods
  • Experience detecting and mitigating bias and unfairness in ML algorithms
  • Experience with Gen AI infrastructure, LLM, and applying generative models to solve problems
  • Familiarity with geospatial data processing and analysis tools
  • Knowledge of water/wastewater treatment processes, asset management principles, and environmental engineering concepts
  • Strong problem-solving abilities and translating business requirements into technical solutions
  • Excellent communication skills to collaborate with cross-functional teams and present findings to different stakeholders
  • Strong sense of innovation and staying updated with advancements in machine learning and environmental engineering

Nice to have

  • Familiarity with geospatial data processing and analysis tools
  • Knowledge of water/wastewater treatment processes, asset management principles, and environmental engineering concepts

Day to day

  • Join a team of data scientists and data engineers working on modern data-driven solutions for the water and wastewater industry
  • Develop and deploy machine learning models for extracting insights from various data sources
  • Collaborate with cross-functional teams to enhance data quality and integrity and develop algorithms for predictive maintenance and process optimization