Remote Geoscience Data Analyst Jobs in Dallas, GA

Charter Global is a global Information Technology and Solutions provider with
more than 19 years of proven track record in gaining customer confidence.
We support our customer needs in Asia-Pacific, Europe and the Americas (North and Latin). Our customers are in a variety of vertical industries: Energy, Finance, Healthcare,
Government, Retail, Fulfillment Logistics, Manufacturing and Telecom.
Charter Global has honed the processes, methodologies, tools and functions to deliver software services via a Global Delivery Model which blends in local and remote resources to get the job done - consistently

Here is the Job details:

Title: Data Scientist

Location: Atlanta, GA / Dallas, TX

Duration: 12+ Months

Job Description:

Oversees and performs end-top-end data based research. Design data mining solutions to be implemented and executed with alignment to the planned scope and design coverage and needs/uses, leveraging knowledge and a broad understanding of E2E business processes and requirements.

Defines the data analytics research plan, scope and resources required to meet the objectives of his/her area of ownership (segments of the project/engagement). This includes:- Analyzing the data and identifying data sources- Determining appropriate types of data analytics to be performed- Selecting and applying data analysis techniques to ensure that recommendations and predictions provide an adequate level of confidence based on defined coverage criteria- Designing repeatable, verifiable and traceable analytical models

Identifies and analyses new data analytic directions and their potential business impact to determine the proper prioritization of data analytics activities based on business needs and analytics ROI.

Identifies data sources, oversees the data collection process and designs the data structure in collaboration with data experts (BI or big-data) and subject matter and business experts. Ensures that data used in the data analysis activities are of the highest quality.

Constructs data models (algorithms and formulas) for required business needs and predictions.

Works closely with content experts and managers to pinpoint queries, map data, and validate results. Maintains and enhances the professional and business relationship with internal stakeholders.

Facilitates presentations on how to use the data. Offers practical solutions to be used by the end decision makers.

Presents results, including the preparation of patents and white papers and facilitating presentations during conferences.

Effectively participates in and/or leads formal and informal reviews with stakeholders, applying knowledge and experience and providing insights from a professional perspective.

Prepares results in such a way they will be convenient for use. Provides professional support for team members and keeps them informed of assignments/ project status. Provides for training and support for other team members.

Explores and examines data from multiple sources. The Data Scientist sifts through all incoming data with the goal of discovering previously hidden insights, which, in turn, can provide a competitive advantage or address a pressing business problem. A Data Scientist does not simply collect and report on data, but also looks at it from many angles, determines what it means, and then recommends ways to apply the data.

Participates in technical designs of the wrapped product, which will run the model. Ensures that the model is properly used, that data inputs are supplied correctly and in a timely manner. Verifies that the correct data population is being processed. Ensures that that the output of the model is used correctly and that business objectives are being targeted.

Participates in the development stages of the wrapped product, including design, development, QA, implementation and production. This is particularly critical when the Development and Implementation teams find it difficult to understand and evaluate the model's objectives and benefits)

Critical Experiences:

Masters in mathematics, statistics or computer science or related field - Ph D. degree preferred

5 or more years of relevant quantitative and qualitative research and analytics experience

Solid knowledge of statistical techniques

The ability to come up with solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets

Strong programming skills (such as Hadoop MapReduce or other big data frameworks, Java), statistical modeling (like SAS or R)

Experience using machine learning algorithms

High proficiency in the use of statistical packages

Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms

Strong communication and interpersonal skills

Knowledge of telecommunications and of the subject area being investigated - advantage.

Technical Expertise