Data Scientist - Predictive Modeling/python/r

Job Description

• Role Summary :, , - The Data Scientist will be responsible for developing valuable algorithms, rules, KPIs and reports, working cross-functionally with Engineering, GRC, ITPE and others to address statistical, machine learning and data mining problems in an applied research environment
• , , - In this role, you will apply modern machine learning and statistical methods for finding structure and value in both large and small data sets
• , Essential Responsibilities :, , , - Identify data sets required to develop predictive models for solving internal and external business problems, , , - Explore data sets and identify data transformation and data quality needs for targeted applications, , , - Develop algorithms and predictive models to derive insights and business value from data, , , - Test and validate algorithms and models using statistical and other techniques, , , - Effectively communicate technical analyses and results to business management, , , - Protect the Intellectual Property rights of the company, , , - Work with technical teams in application and deployment of data mining methods, , , - Perform exploratory, and targeted data analyses, , , - Ensure proper definition of data needs, evaluation of data quality, and critique appropriate statistical analyses; for critical projects, perform needed analyses, , , - Ensure proper definition of data needs, evaluation of data quality, and critique appropriate statistical analyses
• , , Quality Specific Goals :, , , - Aware of and comply with the Quality Manual, Quality Management System, Quality Management Policy, Quality Goals, and applicable laws and regulations as they apply to this job type/position, , - Complete all planned Quality & Compliance training within the defined deadlines, , - Identify and report any quality or compliance concerns and take immediate corrective action as required, , - Lead continuous improvement activities by driving the implementation of process and product quality improvement initiatives. , Qualifications/Requirements :,- Bachelor's degree in Computer Science, Mathematics, or Engineering, or closely related fields,- Minimum of 5-7 years of experience in data, analytics, or related industry,- Practical understanding of the Data modeling concepts,- Experience in one or more analytics software tools and packages e.g. R, Python etc,- Experience with SQL and one RDBMS product (Oracle, Teradata etc.),- Experience in software development and the software development lifecycle,- Ability to clearly communicate program status, issues, risks, plans, etc. to leadership,- Proven ability to create and maintain online and printed documentation,- Effective team player and contributor with solid communication skills in interfacing with both team members and management,- Able to simplify strategy into specific actions with clear accountability, make decisions with speed and accuracy based on best available information, and communicate priorities clearly and concisely
• - Extremely knowledgeable in data concepts and technologies
• Desired Characteristics :,- Experience with Linux/Unix operating system, shell script, and perl,- Experience with one BI visualization software (Tableau, Spotfire, etc.),- Experience with data extraction, data cleansing, data manipulation, ETL tools, and big data technologies, data dictionaries, and data management processes,- Global mindset with ability to effectively work on distributed remote teams,- Familiarity with IT Systems and software development,- Experience / familiarity with Remote Monitoring & Diagnostics,- Strong communication skills with ability to communicate effectively / clearly at different levels in the organization,- Ability to work well in team environment - PhD. in Computer Science, Mathematics, Applied Statistics OR in STEM Majors (Science, Technology, Engineering and Math),- Experience to apply theoretical knowledge to solve industrial problems,- Experience with integrated Big Data programming environments and Competency in major analytics software packages and programming environments (e.g. Hadoop / Map-Reduce, Mahout; Python, R, Java etc. in Big data paradigms).

Job Summary