Data Scientist/Machine Learning Engineer
Job Description:
Job description:
**MUST BE US CITIZEN OR GREEN CARD HOLDER**
We are looking for a experienced Data Scientist/Machine Learning Engineer.
1. Must have a Master's Degree in any of the these field - Mathematics, Statistics, Computer Science, Data Science, Engineering or related field.
2. At least 5 Years of industry Experience with machine learning algorithms and frameworks like scikit-learn, TensorFlow, and PyTorch.
3. Programming Proficiency: Expertise in programming languages such as Python, R, and SQL for data manipulation and analysis.
4. Statistical Analysis: Strong understanding of statistics and probability to develop and validate models.
5. Data Wrangling: Ability to clean, organize, and preprocess large datasets for analysis.
6. Data Visualization: Proficiency in visualization tools such as Matplotlib, Seaborn, and Tableau to present insights clearly.
7. Database Management: Knowledge of database systems and SQL for efficient data retrieval and storage.
8. Domain knowledge: Understanding of the specific industry domain to contextualize data insights and make relevant recommendations.
9. Communication Skills: Ability to effectively communicate complex data findings to non-technical stakeholders.
ABOUT AD-HOC RESEARCH
Ad-Hoc Research specializes in providing the full spectrum of Systems Engineering services to major DOD acquisition programs and Research & Development projects. Our company believes in inducing innovations through focused research. We are an army veteran owned 8a company with defense contracts in many states. We are also launching a cyber range platform to provide customer support to our army and defense clients. Our data science team supports a major telecom company to develop and operationalize AI/ML models. We have a lot of exciting opportunities to grow and be successful in our fast growing company!
Ad-Hoc Research is an Equal Opportunity Employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or national origin.