Find Jobs

Description

This entry Data Scientist role is responsible for the collecting, cleaning and munging ofdatain ways to determine the value of the data and extract that value for discovery and decision support. Our data scientist are part detectives and business analysis. The detective work comes in handy when parsing, clustering, and stratifying the data to find and amplify signals in the data. The business analysis is used to determine what signals they should look for based their understanding of the client's business goals for collecting the data.

Primary Responsibilities

The candidate will be responsible for handling the extract, transform, and load (ETL) for multi-domain data. They will be applying various machine learning algorithms to the multi-domain data to measure the performance of the algorithm and the suitability of the training data. The candidates will work with convolutional neural nets, deep neural nets, federated learning, computer vision, reinforcement learning, autoencoders, and a host of natural language algorithms including Stanford CoreNLP, Spacy, NLTK, Word2Vec and Gensim along transformer models like BERT. With those models and libraries, the candidate will explore subjects like domain adaptive prototypes to examine the operational capabilities of bi-directional learning, multimodal learning, model fusion, and continuous learning both with supervised and unsupervised approaches.

Basic Qualifications

The candidate must be a self-starter and self-assessing to know when to seek assistance. Also, the position requires a candidate who can communicate well with the ability to present their work to internal and external groups. The candidate must actively continuously learn new skills in data science and machine learning. The candidate will also have the following.

• Bachelor's degree in Computer Science, Data Science or related field and at least 2 years of relevant experience (including coursework)

• Good understanding of machine learning algorithms, tools and platforms

• Experience in at least three of these Toolkits: NumPy, SciPy, scikit-learn, TensorFlow, Pytorch, Keras, Genism, vow pal wabbit, Stanford CoreNLP, , etc.

• Understanding of programming fundamentals

• Python proficiency

• Self-starter and intellectual curiosity

• Great communication skills, ability to explain predictive analytics to non-technical audience

• Proficiency in data exploration techniques and tools

• Must be able to obtain TS/SCI with CI Poly security clearance.

Preferred Qualifications

• Experience programming machine learning algorithms for GPUs

• Working knowledge of DNN, CNN, GCN, and RNN

• Trained transfer learning models

• Knowledge in applying federated learning

• Practical utilized model fusion

• Ability to work with graph data for machine learning

• Understanding of containers (like Docker) and notebooks (like Jupyter)

• Discernment of when and how to use machine learning regulation

• Practice with reinforcement learning

• Experience programming machine learning algorithms for GPUs

• Expertise with AWS Command Line Interface, Simple Cloud Storage, Elastic Compute Cloud, Virtual Private Cloud, and Identity and Access Management

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

#RemoteSan Diego, CA, US, 92189Posted 9 hours ago