HOPES FOREVER CONSULTANCY PVT. LTD.
Data Scientist - Full Time at Newark
HOPES FOREVER CONSULTANCY PVT. LTD., Newark, New Jersey, us, 07175
Job Description: Data Scientist
Title:
Data Scientist Location:
Newark The Data Scientist will harness vast amounts of data to optimize business results. He/she will exercise their knowledge of descriptive and multivariate statistical techniques and applications, and database analysis tools and techniques to develop strategic insights to drive business goals. Works hard at advancing the state-of-the-art in how data is applied to solve problems in the Public Transportation industry. Will also be responsible for teaching data analysts and software engineers how to work effectively with vast quantities of data. This is a fairly senior and specialized position, so we could go as high as 120-140k for this role. (Salary + Benefits) Responsibilities
Work with cross departmental team to define metrics, guidelines, and strategies for effective use of algorithms and data. Identify, design, and build appropriate datasets for the identification of complex data patterns and analytics. Create data mining and analytics architectures, coding standards, statistical reporting, and data analysis methodologies. Establish links across existing data sources and find new, interesting mash-ups. Coordinate data resource requirements between analytics, application teams, and business stakeholders. Work with product managers, engineers, and analytics team members to translate prototypes into production. Assist in the development of data management policies and procedures. Develop best practices for analytics instrumentation and experimentation. Conduct research and make recommendations on big data infrastructure, database technologies, analytics tools, services, protocols, and standards in support of procurement and development efforts. Drive the collection of new data and the refinement of existing data sources. Develop algorithms and predictive models to solve critical business problems. Analyze historical data, identify patterns, and come up with predictive, prescriptive, descriptive, and cognitive analytics. Develop tools and libraries that will help analytics team members more efficiently interface with huge amounts of data. Analyze large, noisy datasets and identify meaningful patterns that provide actionable results. Develop and automate new enhanced imputation algorithms. Create informative visualizations that intuitively display large amounts of data and/or complex relationships. Provide and apply quality assurance best practices for data science services across the organization. Develop, implement, and maintain change control and testing processes for modifications to algorithms and data analytics. Collaborate with database and disaster recovery administrators to ensure effective protection and integrity of data assets. Manage and/or provide guidance to junior members of the analytics team. Develop scalable, efficient, and automated processes for large scale data analyses and model development, validation, and implementation. Collaborate with internal and external business and data teams, data engineers, and analysts. Qualifications
Minimum 5 years' experience in modeling and analysis; graduate or postgraduate university degree in the field of computer science, mathematics, or statistics, Data Science and/or 10 years + equivalent work experience. Well versed with CRISP-DM methodology and reference model. Very hands-on with a proven track record of successful Data Science implementations from industry, preferably Public Transportation and Travel industry. Advanced knowledge in one or more of the following: Linear and Non-Linear Models, Time Series Analysis, Random Forest, SVM, Neural Networks, Unsupervised Methods (Dimensionality Reduction, Clustering, etc.). Machine Learning, including Deep Learning. Advanced knowledge in R and Python. Advanced experience with SQL skills. Must be able to perform impact data analysis and data profiling on source data systems and determine the best way to model data. Employ data visualization tools where appropriate (ggplot, Tableau, ThinkCell, etc.). Ability to communicate project requirements and modeling outcomes to technical and non-technical audiences. Ability to work in a self-directed and team environment. Extensive experience solving analytical problems using quantitative approaches. Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources. Well versed with Git. Must have machine learning and AI expertise. Familiarity with relational, SQL, and NoSQL databases. Good working knowledge of reporting analytical tools like Tableau, Power BI. Experience with very large datasets is a must. Experience in programming with JAVA, Perl, C. Good understanding of the organization's goals and objectives. Knowledge of applicable data privacy practices and laws. A strong passion for empirical research and for answering hard questions with data. A flexible analytic approach that allows for results at varying levels of precision. Good written and oral communication skills. Strong technical documentation skills. Good interpersonal skills. Highly self-motivated and directed. Keen attention to detail. Ability to effectively prioritize and execute tasks in a high-pressure environment. Experience working in a team-oriented, collaborative environment.
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Title:
Data Scientist Location:
Newark The Data Scientist will harness vast amounts of data to optimize business results. He/she will exercise their knowledge of descriptive and multivariate statistical techniques and applications, and database analysis tools and techniques to develop strategic insights to drive business goals. Works hard at advancing the state-of-the-art in how data is applied to solve problems in the Public Transportation industry. Will also be responsible for teaching data analysts and software engineers how to work effectively with vast quantities of data. This is a fairly senior and specialized position, so we could go as high as 120-140k for this role. (Salary + Benefits) Responsibilities
Work with cross departmental team to define metrics, guidelines, and strategies for effective use of algorithms and data. Identify, design, and build appropriate datasets for the identification of complex data patterns and analytics. Create data mining and analytics architectures, coding standards, statistical reporting, and data analysis methodologies. Establish links across existing data sources and find new, interesting mash-ups. Coordinate data resource requirements between analytics, application teams, and business stakeholders. Work with product managers, engineers, and analytics team members to translate prototypes into production. Assist in the development of data management policies and procedures. Develop best practices for analytics instrumentation and experimentation. Conduct research and make recommendations on big data infrastructure, database technologies, analytics tools, services, protocols, and standards in support of procurement and development efforts. Drive the collection of new data and the refinement of existing data sources. Develop algorithms and predictive models to solve critical business problems. Analyze historical data, identify patterns, and come up with predictive, prescriptive, descriptive, and cognitive analytics. Develop tools and libraries that will help analytics team members more efficiently interface with huge amounts of data. Analyze large, noisy datasets and identify meaningful patterns that provide actionable results. Develop and automate new enhanced imputation algorithms. Create informative visualizations that intuitively display large amounts of data and/or complex relationships. Provide and apply quality assurance best practices for data science services across the organization. Develop, implement, and maintain change control and testing processes for modifications to algorithms and data analytics. Collaborate with database and disaster recovery administrators to ensure effective protection and integrity of data assets. Manage and/or provide guidance to junior members of the analytics team. Develop scalable, efficient, and automated processes for large scale data analyses and model development, validation, and implementation. Collaborate with internal and external business and data teams, data engineers, and analysts. Qualifications
Minimum 5 years' experience in modeling and analysis; graduate or postgraduate university degree in the field of computer science, mathematics, or statistics, Data Science and/or 10 years + equivalent work experience. Well versed with CRISP-DM methodology and reference model. Very hands-on with a proven track record of successful Data Science implementations from industry, preferably Public Transportation and Travel industry. Advanced knowledge in one or more of the following: Linear and Non-Linear Models, Time Series Analysis, Random Forest, SVM, Neural Networks, Unsupervised Methods (Dimensionality Reduction, Clustering, etc.). Machine Learning, including Deep Learning. Advanced knowledge in R and Python. Advanced experience with SQL skills. Must be able to perform impact data analysis and data profiling on source data systems and determine the best way to model data. Employ data visualization tools where appropriate (ggplot, Tableau, ThinkCell, etc.). Ability to communicate project requirements and modeling outcomes to technical and non-technical audiences. Ability to work in a self-directed and team environment. Extensive experience solving analytical problems using quantitative approaches. Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources. Well versed with Git. Must have machine learning and AI expertise. Familiarity with relational, SQL, and NoSQL databases. Good working knowledge of reporting analytical tools like Tableau, Power BI. Experience with very large datasets is a must. Experience in programming with JAVA, Perl, C. Good understanding of the organization's goals and objectives. Knowledge of applicable data privacy practices and laws. A strong passion for empirical research and for answering hard questions with data. A flexible analytic approach that allows for results at varying levels of precision. Good written and oral communication skills. Strong technical documentation skills. Good interpersonal skills. Highly self-motivated and directed. Keen attention to detail. Ability to effectively prioritize and execute tasks in a high-pressure environment. Experience working in a team-oriented, collaborative environment.
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