Sr Data Scientist

Optimal Solutions & Technologies (OST, Inc.) is focused on excellence. We specialize in providing Management Consulting, Information Technology, and Research Development and Engineering services. 

The fundamental distinction of the OST team is its business knowledge in both the public and private sectors. We serve the aerospace & transportation, association & nonprofit, defense, education, energy, financial, healthcare, and technology & telecommunications industries. OST is successful because we listen to our clients, we learn from our clients, and we know our clients.

Sr. Data Scientist 

Job Duties (Description of specific duties on a typical workday for this position):

• Contribute to the solution architecting process for data science use cases,
• Collect and ingest data from multiple resources, transform and prepare large data sets, analyze and visualize to gain insights and trends, report and present the analysis results, and maintain databases and information by using OST’s analytical technology stack,
• Build, deploy and maintain data analytics / artificial intelligence-machine learning (AI/ML) applications for business use cases,
• Contribute to OST’s growth operations and project re-competes by providing analytics related technical volumes, and preparing customer facing demos and presentations,
• Support project teams to optimize their processes, reduce the project risks and enable the added value delivery by employing continuous improvement process by utilizing descriptive, diagnostic, predictive and prescriptive analytics methods,
• Support OST and project level Data Governance / Management efforts as a data steward/custodian by defining KPIs for measurement analysis, maintaining measurement and analysis repository, updating data definitions & metadata, defining data standards, and monitoring data quality,
• Promote data analytics as a disruptive technology of today; prepare course catalogs & materials, and provide training to OST’ians and our clients,
• Represent OST in data science related seminars and conferences.

Requirements (Years of experience, Education, Certifications):

• Minimum 5 years of experience,
• Education: BA or BS degree in Information Management, Data Science, Computer Science, Statistics, Mathematics, Bioinformatics, or other related field.
• Quantitative skills: Analytical and problem-solving aptitude, demonstrated experience on conducting end-to-end analytics; data ingestion, engineering, analysis and presentation by using computer skills, including demonstrated experience on:
  • Ingestion of hot and cold data from multiple sources,
  • Data preparation – data cleaning, tidying, data transformation and integration,
  • Data modeling with relational and non-relational databases,
  • Descriptive and inferential statistics experience, including hypothesis testing, multi-variate data analysis and exploratory data analysis, and data visualization,
  • Predictive and prescriptive modeling, including statistical modeling, AI/ML techniques, linear and non-linear optimization methods,
• Technical skills: Demonstrated knowledge on using software tools, including:
  • Conducting analysis and developing analytics/AI/ML applications with cloud data management and analytics platforms such as AWS or Azure,
  • Conducting data engineering by using Data Extraction, Transforming and Loading (ETL) tools, such as Excel, AWS Glue, SAS Viya, R and Python data wrangling libraries,
  • Querying data with tools such as MS SQL, AWS Aurora, PostgreSQL, and MySQL, SAS Viya
  • Statistical tools, such as R or Python statistical & machine learning libraries, Minitab, SAS Viya, SPSS and @Risk,
  • Visualizing and reporting with tools such as PowerBI, Tableau, SAS Viya, R Shiny, Python Plotly,
• Research skills: Undertake in-depth research, quantify the information and produce qualitative and quantitative reports and presentations,
• Communication and Presentation skills: Verbal and written communication skills to converse and collaborate with all levels of employees, present the analysis findings and technical matters clearly via reports and oral presentations to clients and senior management,
• Organizational skills: Work under tight schedules, effectively manage and prioritize multiple work assignments,
• Learning skills: Eager to ask questions, ability to take guidance and provide feedback, eager to learn and advance technical knowledge and skills,
• Team work abilities: Work effectively in a team oriented environment, as well as independently in a fast-paced, and changing environment,
• Attention to detail: Pay meticulous attenti