Data Scientist - CiviTronix : Job Details

Data Scientist

CiviTronix

Job Location : Boston,MA, USA

Posted on : 2025-08-08T01:03:25Z

Job Description :

About the job Data ScientistWhy CiviTronix?At CiviTronix, we believe that data-driven decision-making is at the heart of innovation in the engineering industry. As a Data Scientist, you will have the opportunity to make a direct impact on our projects, processes, and client outcomes by leveraging the power of data. You'll be working in a dynamic, collaborative environment that encourages continuous learning and professional development.Note: Strictly for candidates within the United States only.The Data Scientist will be responsible for analyzing large sets of structured and unstructured data to uncover actionable insights, support decision-making, and solve complex problems across a variety of engineering and infrastructure domains. You will leverage advanced statistical, mathematical, and machine learning models to derive insights that enhance project outcomes, improve efficiencies, and contribute to the long-term success of CiviTronix's operations.As a Data Scientist at CiviTronix, you will work closely with engineering, project management, and business teams to identify opportunities for data-driven improvements. This role offers an exciting opportunity to be at the forefront of applying data science to optimize engineering solutions, predict system behaviors, and support strategic business decisions.Key Responsibilities:

  • Data Collection & Preparation:
    • Collect, clean, and preprocess data from various internal and external sources, including engineering reports, sensors, geospatial data, environmental data, and more.
    • Develop and maintain data pipelines that ensure efficient data storage, retrieval, and processing for analysis.
    • Collaborate with teams across the organization to identify relevant data sources and ensure data quality and integrity.
  • Advanced Data Analysis & Modeling:
    • Apply advanced statistical methods and machine learning algorithms to analyze complex datasets and generate insights that drive business value.
    • Develop predictive models and algorithms for engineering applications such as project forecasting, resource allocation, risk management, and performance optimization.
    • Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies within datasets, providing actionable insights to stakeholders.
  • Collaboration with Engineering Teams:
    • Work closely with engineering teams to understand their data needs, translate business problems into data science solutions, and identify opportunities for data-driven process improvements.
    • Support engineering teams by providing data-driven recommendations and insights for decision-making, performance optimization, and risk mitigation.
  • Data Visualization & Reporting:
    • Create compelling visualizations and dashboards to communicate complex data insights to both technical and non-technical stakeholders.
    • Use tools like Tableau, Power BI, or custom-built solutions to present results in a clear and actionable manner.
    • Prepare reports that summarize findings, recommendations, and impact, and present them to senior leadership, project managers, and clients.
  • Machine Learning & Automation:
    • Design, build, and deploy machine learning models that automate decision-making processes or improve operational efficiencies across projects and teams.
    • Evaluate and fine-tune models over time to ensure they provide the best possible predictions and insights.
    • Work with software engineers and developers to deploy models into production environments and ensure their scalability and performance.
  • Predictive & Prescriptive Analytics:
    • Build predictive models to forecast key metrics and outcomes, such as project costs, timelines, resource needs, and environmental impact.
    • Develop prescriptive analytics tools to recommend optimal courses of action based on data-driven insights, improving project delivery and client satisfaction.
  • Data Governance & Compliance:
    • Ensure that all data science work is conducted in compliance with company policies, industry regulations, and data privacy laws.
    • Collaborate with the IT and compliance teams to ensure that data is stored securely and adheres to governance standards.
  • Continuous Learning & Innovation:
    • Stay up to date with the latest developments in data science, machine learning, and artificial intelligence to apply cutting-edge techniques to solve business challenges.
    • Continuously evaluate new tools, technologies, and methodologies to improve data analysis capabilities and efficiencies.
  • Cross-Department Collaboration & Support:
    • Collaborate with various teams, including project management, marketing, and finance, to provide insights and support strategic initiatives.
    • Work with business analysts to translate business requirements into data-driven solutions and reports.
    • Required Qualifications:
    • Education:
      • Masters or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
    • Experience:
      • 3+ years of experience in data science, data analysis, or a similar analytical role, ideally within engineering, infrastructure, or technical services.
      • Hands-on experience with machine learning algorithms, statistical modeling, and data analysis techniques.
      • Experience working with large datasets and implementing data processing pipelines.
    • Technical Skills:
      • Strong proficiency in programming languages such as Python, R, or Julia for data analysis and machine learning.
      • Expertise in data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy, TensorFlow, Keras).
      • Solid experience with machine learning frameworks and tools (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
      • Experience with big data tools and platforms (e.g., Hadoop, Spark, AWS, Azure).
      • Knowledge of database technologies (SQL, NoSQL) and data warehousing concepts.
      • Proficiency in data visualization tools like Tableau, Power BI, or similar platforms.
      • Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and related services for data science applications.
    • Analytical & Problem-Solving Skills:
      • Strong ability to analyze complex data, recognize patterns, and draw actionable conclusions.
      • Excellent problem-solving skills, with the ability to break down complex business problems into manageable data science tasks.
    • Communication & Collaboration:
      • Excellent communication skills, with the ability to explain complex data-driven insights to both technical and non-technical stakeholders.
      • Strong teamwork abilities and experience collaborating with cross-functional teams (engineering, product, management).
      • Ability to present data insights clearly through reports, presentations, and visualizations.
    Preferred Qualifications:
    • Experience working in the engineering, infrastructure, or environmental sectors is a plus.
    • Familiarity with geospatial data analysis and tools (e.g., GIS software, spatial analysis techniques) is a plus.
    • Knowledge of optimization techniques for large-scale operations or resource management is a bonus.
    • Experience with automated reporting and business intelligence tools is preferred.
    Pay rate: $55.00 - $72.00 / hourLocation: Remote (United States Only)Benefits
    • 401(k)
    • 401(k) matching
    • Health insurance
    • Dental insurance
    • Life insurance
    • Paid time off
    Schedule:
    • 8 hour shift
    • Monday to Friday
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