BE A SPARK IN OUR INDUSTRY
JOIN THE METRONOME FAMILY
Every individual has unique passions, career goals, and personal values. We are here to make the connection between those and the needs of our customers. When the stars align, we welcome our new employees - or Pulsers as we like to call them - to the family. We offer competitive benefits to ensure that our Pulsers are well taken care of for whatever comes their way.
Data Scientist - B
- Job Title
- Data Scientist - B
- Requirement ID
- Vienna, VA 22182
- Other Location
The Data Scientist will collect large sets of structured and unstructured data from disparate sources.
- Clean and validate data to ensure accuracy, completeness, and uniformity.
- Analyze data to identify patterns and trends.
- Devise and apply models and algorithms to mine the stores of big data.
- Interpret data to discover solutions and opportunities.
- Use of common machine learning algorithms and problem domains to include feature engineering, hyperparameter tuning, and performance optimization.
- Required Skills
• Bachelor’s degree with 3-7+ years of related experience.
• Experience with SQL for advanced querying and joining of heterogeneous data sets.
• Proficient with R and Python; Standard machine learning packages such as panda and sklearn; Agile processes and procedures
• Graph analytics experience, using software such as iGraph and NetworkX
• Familiar with common algorithms for community detection and node embeddings
• Experience modeling tabular, unstructured, and semi-structed data as a graph
• Experience with Graph databases (e.g. Neo4j) and relevant query and management skills
• Experience with NLP, particular entity extraction
• Experience using existing models and tools, such as Spacy, as well as training new models and evaluating their performance
Active US Government Security Clearance Required.
- Optional Skills
• Advanced candidates will additionally have statistics proficiency including common pitfalls in modeling and data analysis, sampling and data augmentation techniques, and mechanics of common ML algorithms and loss functions
• Experience with existing FINCEN / DARPA analytic tools
• Experience with SAS and other COTS analytic tools highly preferred.