Data Scientist - Droisys

About Company

Droisys is an innovation technology company focused on helping companies accelerate their digital initiatives from strategy and planning through execution. We leverage deep technical expertise, Agile methodologies, and data-driven intelligence to modernize systems of engagement and simplify human/tech interaction.

Amazing things happen when we work in environments where everyone feels a true sense of belonging and when candidates have the requisite skills and opportunities to succeed. At Droisys, we invest in our talent and support career growth, and we are always on the lookout for amazing talent who can contribute to our growth by delivering top results for our clients. Join us to challenge yourself and accomplish work that matters.

Client Description

Our client is a major Fortune 500 company and one of the world’s most innovative and cutting-edge technology companies, and this role is in the Interactive department.

Droisys is seeking Data Scientist job offering onsite hybrid work for a long-term job opportunity in McLean, VA and Meade, MD area of the USA.

Job Description

Job Title Data Scientist

Job Location McLean, VA or Meade, MD [Onsite Work – 4 days onsite every week]

Duration Full Time Employment [Direct Hire Permanent Job]

Required Bachelor’s Degree, TS/SCI with the Polygraph, Data Scientist, R, Python, SAS, or MATLAB, Machine Learning

Salary $180, 000 per annum + benefits + joining bonus

Experience 8 years and above

Position Responsibilities

A data scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.

Required Degree and Experience

• Bachelor's degree in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science) + 7 years of experience, Masters Degree + 5 years of experience, or PhD + 2 years of experience

Required Skills

• Programming experience with data analysis software such as R, Python, SAS, or MATLAB.
• Develop experiments to collect data or models to simulate data when required data are unavailable.
• Develop feature vectors for input into machine learning algorithms.
• Machine Learning/Computer Vision/Object Detection
• Python and/or R
• Identify the most appropriate algorithm for a given dataset and tune input and model parameters.
• Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices).
• Oversee the development of individual analytic efforts and guide team in analytic development process.
• Guide analytic development toward solutions that can scale to large datasets.
• Partner with software engineers and cloud developers to develop production analytics.
• Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation.

Desired Skills

• Prior experience with Pytorch, keras and overhead imagery would be beneficial but not a requirement
• Master’s degree in a technical field (computer science, mathematics, statistics etc) with 1 year of relevant experience
• Bachelor’s degree in a technical field (computer science, mathematics, statistics etc)

Droisys is an equal opportunity employer. We do not discriminate based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. Droisys believes in diversity, inclusion, and belonging, and we are committed to fostering a diverse work environment.