FastTek Global
Data Science and Machine Learning Associate #1034955
FastTek Global, Dearborn, Michigan, United States, 48120
Overview
Dearborn, Michigan — Data Science and Machine Learning Associate #1034955
Job Description:
Responsibilities
Employees in this job function are responsible for predicting and/ or extracting meaningful trends/ patterns/ recommendations from raw data, leveraging data science methodologies including Machine Learning (ML), predictive modeling, math, statistics, advanced analytics, etc.
Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making.
Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data driven decision-making.
Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends.
Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation.
Be able to quickly convert a real business question into a solvable modeling problem, sort out relevant information, and judge the solution against business realities.
Apply business acumen to the problem and solution vs. a solely data-based approach.
Familiarity with Company\'s vehicles, attention to detail, time management, willingness to learn, ability to handle multiple projects at a time, excellent communication and data presentation skills.
Skills
Data Modeling
ALGORITHMS
Python
Big Query
SQL
Microsoft Excel
Microsoft PowerPoint
Statistics
Experience
Associate Exp: Up to 2 years experience in relevant field
Education
Education Required: Master\'s Degree
Education Preferred: Doctorate
Key Responsibilities
Develop and analyze future vehicle pricing and volume forecasts against business plans and scenarios, providing recommendations for effective decision-making.
Create compelling visual representations of data, leveraging effective data storytelling and insights to persuade business partners to act on recommendations.
Collaborate frequently with peers and business partners on diverse data analysis, studies, and projects.
Continuously seek improved approaches and methodologies to evolve our advisory support as the business navigates an ever-changing industry landscape.
Utilize advanced modeling and simulation techniques to generate modeling scenarios to support strategic business decisions, optimizing the performance of Company Business Units.
Apply attribution modeling, statistics, optimization, operation research, machine learning, and other advanced techniques to solve real-world business problems.
Develop analytical methodologies and specify data requirements by translating business phenomena into appropriate mathematical/regression equations
Use \'outside the box\' thinking and modeling to answer difficult questions in an environment with little information and resources
#J-18808-Ljbffr
Job Description:
Responsibilities
Employees in this job function are responsible for predicting and/ or extracting meaningful trends/ patterns/ recommendations from raw data, leveraging data science methodologies including Machine Learning (ML), predictive modeling, math, statistics, advanced analytics, etc.
Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making.
Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data driven decision-making.
Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends.
Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation.
Be able to quickly convert a real business question into a solvable modeling problem, sort out relevant information, and judge the solution against business realities.
Apply business acumen to the problem and solution vs. a solely data-based approach.
Familiarity with Company\'s vehicles, attention to detail, time management, willingness to learn, ability to handle multiple projects at a time, excellent communication and data presentation skills.
Skills
Data Modeling
ALGORITHMS
Python
Big Query
SQL
Microsoft Excel
Microsoft PowerPoint
Statistics
Experience
Associate Exp: Up to 2 years experience in relevant field
Education
Education Required: Master\'s Degree
Education Preferred: Doctorate
Key Responsibilities
Develop and analyze future vehicle pricing and volume forecasts against business plans and scenarios, providing recommendations for effective decision-making.
Create compelling visual representations of data, leveraging effective data storytelling and insights to persuade business partners to act on recommendations.
Collaborate frequently with peers and business partners on diverse data analysis, studies, and projects.
Continuously seek improved approaches and methodologies to evolve our advisory support as the business navigates an ever-changing industry landscape.
Utilize advanced modeling and simulation techniques to generate modeling scenarios to support strategic business decisions, optimizing the performance of Company Business Units.
Apply attribution modeling, statistics, optimization, operation research, machine learning, and other advanced techniques to solve real-world business problems.
Develop analytical methodologies and specify data requirements by translating business phenomena into appropriate mathematical/regression equations
Use \'outside the box\' thinking and modeling to answer difficult questions in an environment with little information and resources
#J-18808-Ljbffr