Data Scientist
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Job Description
Data Scientist at Jensen Hughes leveraging data science techniques for predictive modeling in revenue forecasting and financial analytics. Join a diverse team in a fast-paced remote environment.
Responsibilities:
- 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:
- competitive total rewards package
- retirement plan
- healthcare coverage
- professional development opportunities
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