Jensen Hughes - Data Scientist
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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 buildingand deploying time series models • Familiarity with project management tools such as Jira along with experience incloud platforms and services such as DataBricks or AWS • Proficiency with version control systems such as BitBucket and Pythonprogramming • Experience with big data frameworks such as PySpark along strong knowledge ofdata 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 usingvisualization tools such as Power BI • Strong communication and collaboration skills, with the ability to explain complexconcepts to non-technical audiences • Please note that the salary range provided is a good faith estimate for the position at the time of posting and not a guarantee of compensation. Final compensation may vary based on factors, including but not limited to, responsibilities of the job, education, experience, knowledge, skills, and abilities, geographic location, internal equity, alignment with market data. • Jensen Hughes offers a competitive total rewards package, which includes a retirement plan, healthcare coverage, and a broad range of other benefits. Incentives and/or benefit packages may vary depending on the position and location.
Responsibilities
• Explain complex models (e.g., RandomForest, XGBoost, Prophet, SARIMA) in anaccessible 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 communicateresults 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 todrive data-informed decision-making while also helping in the identification ofopportunities for leveraging data to generate business insights • Enable quick prototype creation for analytical solutions and develop predictivemodels and machine learning algorithms to analyze large datasets and identifytrends • Communicate analytical findings in clear, actionable terms for non-technicalaudiences • Mine and analyze data to improve forecasting accuracy, optimize marketingtechniques, and informed business strategies, developing and managing tools andprocesses for monitoring model performance and data accuracy • Work cross-functionally to implement and evaluate model outcomes
Benefits
• Proficiency in machine learning libraries (statsmodels, prophet, mlflow, scikit-learn, • 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 • $94,800—$142,200 USD
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