Data Scientist / Machine Learning Engineer

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.