Data Scientist
At WTAnow, LLC dba WebTech Analytics, we rely on insightful data to power our systems and solutions. We’re seeking an experienced data scientist to deliver insights on a daily basis. The ideal candidate will have mathematical and statistical expertise, along with natural curiosity and a creative mind. While mining, interpreting, and cleaning our data, this person will be relied on to ask questions, connect the dots, and uncover hidden opportunities for realizing the data’s full potential. As part of a team of specialists, the data scientist will “slice and dice” data using various methods and create new visions for the future.
Objectives of this role
- Collaborate with product design and engineering teams to develop an understanding of needs
- Research and devise innovative statistical models for data analysis
- Communicate findings to all stakeholders
- Enable smarter business processes by using analytics for meaningful insights
- Keep current with technical and industry developments
Job Duties
- Conduct thorough data analysis using SAS, SQL, R, Python, and Excel to draw out important patterns and trends from huge datasets.
- Communicate with SMEs at several levels (technical and functional) to explain findings, create interactive demos/POCs to illustrate concepts, and, as ideas develop, move the concept toward a production solution or product.
- Create the infrastructures necessary to process data from various data sources using Python and Structured Query Language.
- Make sure that raw data is accurate and consistent by preparing and preprocessing it, which will make it acceptable for analysis and modeling.
- Utilize machine learning approaches, create sophisticated predictive models to address business issues including forecasting, categorization, and segmentation.
- Use Tableau to make interactive dashboards and visually appealing visualizations to effectively share information with stakeholders.
- Use statistical techniques to validate hypotheses, do A/B tests, and assess the efficacy of different tactics.
- Keep abreast with the most recent developments in data science and technology to foster innovation and preserve a competitive advantage.
- Make design documents, architecture diagrams, implementation manuals, data dictionaries, and solution documents.
- Create an automated tool leveraging Python's parallel processing capabilities to produce data analysis reports, verify the accuracy of the data, and do data visualization.
- Design and improve the ETL data access pattern with the enterprise data warehouse, upstream and downstream applications, and test the data flow.
- Apply big data technologies to AWS services. to execute the data validation process. Utilize Spark, PySpark, or Scala to implement the functions.
Qualifications
- Master’s degree in Statistics, Data Science/Analytics, Information Systems, or other quantitative science related discipline.
- Demonstrated data manipulation, analysis, and modeling skills in SAS, SQL, R, Python, Tableau and Excel is required
Contact
