Job Description: Pay Range: $60hr - $65hr <ul> <li> 8+ years of analytics experience. </li> <li> Deep Power BI, Tableau technical development skills and expertise. </li> <li> bility to operate independently. </li> <li> Supplier consultants will be experienced in requirements gathering user stories development, data visualization, and technical skills for report building. </li> <li> Consultant should be proficient in understanding business problems and devising reporting solutions including consolidating and creating new reports. </li> </ul> Skill Sets: <ul> <li> Data analysis and data profiling. </li> <li> Requirement elicitation and documentation of reporting requirements. </li> <li> gile Delivery. </li> <li> Power BI Development based on sprint lifecycle including. </li> <li> Grooming of user stories. </li> <li> Sprint planning. </li> <li> Sprint execution. </li> <li> Release to production. </li> <li> Sprint retrospection. </li> <li> SQL and Data Validations. </li> <li> Familiarity with ETL process and tools such as Alteryx. </li> <li> Building scientific and mathematical models using modern technology and machine learning techniques for business analysis. </li> <li> utomate the reports to eliminate the current manual work and improve effectiveness, accuracy and efficiencies. </li> </ul>

Job Description: Pay Range: $60hr - $65hr 8+ years of analytics experience.
Deep Power BI, Tableau technical development skills and expertise.
bility to operate independently.
Supplier consultants will be experienced in requirements gathering user stories development, data visualization, and technical skills for report building.
Consultant should be proficient in understanding business problems and devising reporting solutions including consolidating and creating new reports.
Skill Sets: Data analysis and data profiling.
Requirement elicitation and documentation of reporting requirements.
gile Delivery.
Power BI Development based on sprint lifecycle including.
Grooming of user stories.
Sprint planning.
Sprint execution.
Release to production.
Sprint retrospection.
SQL and Data Validations.
Familiarity with ETL process and tools such as Alteryx.
Building scientific and mathematical models using modern technology and machine learning techniques for business analysis.
utomate the reports to eliminate the current manual work and improve effectiveness, accuracy and efficiencies.

Job Description:

Pay Range: $60hr - $65hr      8+ years of analytics experience.
Deep Power BI, Tableau technical development skills and expertise.
bility to operate independently.
Supplier consultants will be experienced in requirements gathering user stories development, data visualization, and technical skills for report building.
Consultant should be proficient in understanding business problems and devising reporting solutions including consolidating and creating new reports.
Skill Sets:     Data analysis and data profiling.
Requirement elicitation and documentation of reporting requirements.
gile Delivery.
Power BI Development based on sprint lifecycle including.
Grooming of user stories.
Sprint planning.
Sprint execution.
Release to production.
Sprint retrospection.
SQL and Data Validations.
Familiarity with ETL process and tools such as Alteryx.
Building scientific and mathematical models using modern technology and machine learning techniques for business analysis.
utomate the reports to eliminate the current manual work and improve effectiveness, accuracy and efficiencies.

Job Description: Responsibilities: <ul> <li> Design and develop algorithms and models to use against large datasets to create business insights. </li> <li> Incorporate business knowledge into solution approach by trustful collaboration with internal customers and cross-functional teams. </li> <li> Lead Data Science & Analytics projects & initiatives and work independently on solution development; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies; Prepare reports, updates and presentations related to progress made on a project or solution. </li> <li> Effectively communicate insights, recommendations and its impact to both technical and non-technical leaders and business partners. </li> <li> Participate in establishing and continuously improving Magnas data science practice by developing replicable solutions (e.g. codified data products, recipes, project documentation, process flowcharts). </li> <li> Seek further knowledge on key developments within data science, technical skill sets, and additional data sources. </li> <li> Regular travel is not to exceed 15%. </li> <li> 3+ years of practical experience with data science / processing and analytics. </li> <li> Experience in Manufacturing domain: smart manufacturing / smart factory / Industry 4.0 / OEE (overall equipment efficiency). </li> <li> bility to sift through data, identify critical information, analyze, develop hypothesis and make recommendations to broader audience required. </li> <li> Experience developing and running simulation, optimization, and what-if scenario planning tools to support decision making. </li> <li> Experience building and maintaining predictive and/or prescriptive models in production at enterprise scale. </li> <li> dvanced knowledge and engineering skills in (Cloud) big data & database technologies, data management & data pipeline development. </li> <li> Experience with Microsoft Azure stack (Azure Data Warehouse, Databricks, Azure Analysis Services, Power BI) is an advantage. </li> <li> dvanced degree, applicable certification, or equivalent experience in Operations Research, Management Science, Industrial and Systems Engineering, Statistics, Mathematics, Economics, Computer Science or related field. </li> </ul>

Job Description: Pay Range: $45hr - $60hr Responsibilities: <ul> <li> Extract and transform analytical chemistry data from public sources into spreadsheet templates that are loaded by others into a database. </li> <li> thorough knowledge of analytical chemistry data and methods is needed to accurately extract and transform source data in preparation for database assimilation. </li> <li> Provide technical knowledge of analytical chemistry data and methods to support the data management team </li> <li> Coordinate activities with data source subject matter experts to ensure integration, data integrity and data quality. </li> <li> Work with both business and technology team members. </li> <li> Work independently. </li> </ul> Minimum Requirements: <ul> <li> BS in Chemistry. </li> <li> 5+ years of related work experience in management of analytical data. </li> <li> Good written and verbal communication skills. </li> <li> Team player, collaborative. </li> <li> Critical thinker, good problem solver. </li> </ul>

Job Description: Pay Range: $91.98hr $96.98hr Responsibilities: <ul> <li> Leads conversations with business stakeholders and subject matter experts to understand business and subject matter context. </li> <li> Scopes and prioritizes modeling work to deliver business value. </li> <li> pplies data science, machine learning and other analytical modeling methods to develop defensible and reproducible predictive models. </li> <li> Serves as the technical lead for the development of computer vision models, leading data labeling, model training and model evaluation. </li> <li> Extracts, transforms, and loads data from dissimilar sources from across Client for model-building and analysis. </li> <li> Writes and documents python code for data science (feature engineering and machine learning modeling) independently. </li> <li> Documents and presents data science experiments and findings clearly to other data scientists and business stakeholders. </li> <li> ct as peer reviewer of models and analyses built by other data scientists. </li> <li> Develops and presents summary presentations to business. </li> <li> Present findings and makes recommendations to officers and cross-functional management. </li> <li> Build and maintain strong relationships with business units and external agencies. </li> <li> Works with cross functional teams, including data engineers, machine learning engineers, data scientists, and subject matter experts. </li> </ul> Education Minimum: <ul> <li> Bachelor's degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field. </li> </ul> Education Desired: <ul> <li> Master's degree in one of the above areas. </li> </ul> Experience Minimum: <ul> <li> 4 years in data science for business (or 2 years, if possess master's degree, as described above). </li> </ul> Knowledge, Skills, Abilities and Technical Competencies: <ul> <li> Demonstrated knowledge of and abilities with data science standards and processes (model evaluation, optimization, feature engineering, etc.) along with best practices to implement them. </li> <li> Competency in software engineering, statistics, and machine learning techniques as they apply to data science deployment. </li> <li> Competency in commonly used data science and/or operations research programming languages, packages, and tools. </li> <li> Hands-on and theoretical experience of data science/machine learning models and algorithms. </li> <li> bility to synthesize complex information into clear insights and translate those insights into decisions and actions. </li> <li> Demonstrated ability to explain in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines. </li> <li> Competency in the mathematical and statistical fields that underpin data science. </li> <li> Mastery in systems thinking and structuring complex problems. </li> <li> bility to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies. </li> </ul> Desired: <ul> <li> Experience building computer vision models. </li> <li> Experience with AWS technologies (S3, Ground Truth, Sagemaker). </li> </ul>

Job Description: Responsibilities: <ul> <li> Design and develop algorithms and models to use against large datasets to create business insights. </li> <li> Incorporate business knowledge into solution approach by trustful collaboration with internal customers and cross-functional teams. </li> <li> Lead Data Science & Analytics projects & initiatives and work independently on solution development; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies; Prepare reports, updates and presentations related to progress made on a project or solution. </li> <li> Effectively communicate insights, recommendations and its impact to both technical and non-technical leaders and business partners. </li> <li> Participate in establishing and continuously improving Magnas data science practice by developing replicable solutions (e.g. codified data products, recipes, project documentation, process flowcharts). </li> <li> Seek further knowledge on key developments within data science, technical skill sets, and additional data sources. </li> <li> Regular travel is not to exceed 15%. </li> <li> 3+ years of practical experience with data science / processing and analytics. </li> <li> Experience in Manufacturing domain: smart manufacturing / smart factory / Industry 4.0 / OEE (overall equipment efficiency). </li> <li> bility to sift through data, identify critical information, analyze, develop hypothesis and make recommendations to broader audience required. </li> <li> Experience developing and running simulation, optimization, and what-if scenario planning tools to support decision making. </li> <li> Experience building and maintaining predictive and/or prescriptive models in production at enterprise scale. </li> <li> dvanced knowledge and engineering skills in (Cloud) big data & database technologies, data management & data pipeline development. </li> <li> Experience with Microsoft Azure stack (Azure Data Warehouse, Databricks, Azure Analysis Services, Power BI) is an advantage. </li> <li> dvanced degree, applicable certification, or equivalent experience in Operations Research, Management Science, Industrial and Systems Engineering, Statistics, Mathematics, Economics, Computer Science or related field. </li> </ul>

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