Data Scientist, Finance & Accounting – Forecasting

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October 20

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Jensen Hughes

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Security • Engineering • Risk Management

Jensen Hughes is a global leader in safety, security, and risk-based engineering and consulting. They provide an extensive range of services, including fire protection engineering, accessibility consulting, risk and hazard analysis, forensic investigations, and security risk consulting. With a significant global presence, they operate in various sectors, such as government, healthcare, science and technology, and energy. Jensen Hughes is widely recognized for its expertise in fire protection engineering, a legacy it has been known for since 1939, and it continues to advance its commitment to making the world safe, secure, and resilient.

1001 - 5000 employees

Founded 1939

🔐 Security

📋 Description

• Apply statistical techniques (regression, distribution analysis, hypothesis testing) to derive insights from data and create advanced algorithms and statistical models such simulation, scenario analysis, and clustering • Explain complex models (e.g., RandomForest, XGBoost, Prophet, SARIMA) in an accessible way to stakeholders • Visualize and present data using tools such as Power BI, ggplot, and matplotlib • Explore internal datasets to extract meaningful business insights and communicate results effectively and write efficient, reusable code for data improvement, manipulation, and analysis • Manage project codebase using Git or equivalent version control systems • Design scalable dashboards and analytical tools for central use • Build strong collaborative relationships with stakeholders across departments to drive data-informed decision-making while also helping in the identification of opportunities for leveraging data to generate business insights • Enable quick prototype creation for analytical solutions and develop predictive models and machine learning algorithms to analyze large datasets and identify trends • Communicate analytical findings in clear, actionable terms for non-technical audiences • Mine and analyze data to improve forecasting accuracy, optimize marketing techniques, and informed business strategies, developing and managing 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 related technical field • 3+ years of relevant experience in data science and analytics and adept in building and deploying time series models • Familiarity with project management tools such as Jira along with experience in cloud platforms and services such as DataBricks or AWS • Proficiency with version control systems such as BitBucket and Python programming • Experience with big data frameworks such as PySpark along strong knowledge of data cleaning packages (pandas, numpy) • Proficiency in machine learning libraries (statsmodels, prophet, mlflow, scikit-learn, 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 along with experience using visualization tools such as Power BI • Strong communication and collaboration skills, with the ability to explain complex concepts to non-technical audiences

🏖️ Benefits

• Opportunity to grow within a supportive and collaborative team environment • Access to training and development programs to enhance your payroll expertise • Career advancement with an established framework is in place – clearly defining expectations and outlining opportunities for advancement