Jensen Hughes

Jensen Hughes

Jensen Hughes is a global leader in safety, security, and risk-based engineering and consulting services for the built environment. With a team of engineers, scientists, and consultants, they offer a wide range of services including fire protection sys...

Construction & Engineering
1K-5K
Founded 1980

Description

  • Apply statistical techniques to derive insights from data and build advanced algorithms and statistical models.
  • Develop and explain predictive models such as RandomForest, XGBoost, Prophet, and SARIMA to stakeholders.
  • Visualize and present data using tools such as Power BI, ggplot, and matplotlib.
  • Explore internal datasets, communicate business insights, and write efficient, reusable code for data analysis and improvement.
  • Manage the project codebase using Git or equivalent version control systems.
  • Design scalable dashboards and analytical tools for central use.
  • Build collaborative relationships with stakeholders across departments to support data-informed decision-making.
  • Create quick prototypes for analytical solutions and develop predictive models and machine learning algorithms for large datasets.
  • Communicate analytical findings in clear, actionable terms for non-technical audiences.
  • Mine and analyze data to improve forecasting accuracy, optimize marketing techniques, and support business strategy.
  • Develop and manage tools and processes for monitoring model performance and data accuracy.
  • Work cross-functionally to implement and evaluate model outcomes.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related technical field.
  • 3+ years of relevant experience in data science and analytics.
  • Experience building and deploying time series models.
  • Familiarity with project management tools such as Jira.
  • Experience with cloud platforms and services such as DataBricks or AWS.
  • Proficiency with version control systems such as BitBucket and with Python programming.
  • Experience with big data frameworks such as PySpark.
  • Strong knowledge of data cleaning packages such as pandas and numpy.
  • Proficiency in machine learning libraries such as statsmodels, prophet, mlflow, scikit-learn, and pyspark.ml.
  • Knowledge of statistical and data mining techniques such as GLM/regression, random forests, boosting, and text mining.
  • Competence in SQL and relational databases.
  • Experience using visualization tools such as Power BI.
  • Strong communication and collaboration skills, including the ability to explain complex concepts to non-technical audiences.

Benefits

  • Remote role based in the U.S.
  • Competitive total rewards package.
  • Retirement plan.
  • Healthcare coverage.
  • Salary range of $94,800 to $142,200 USD.
  • Potential variation in compensation based on role responsibilities, experience, location, and market alignment.

Interested in this position?

Apply directly on the company website

Apply Now

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