About the position

Title

Data Scientist Machine Learning Engineer

Reports To

CTO

Job Purpose

Bright Apps LLC is seeking a driven, creative, inquisitive, and focused Data Scientist to join our team. This role will support Bright Apps LLC, lending technical knowledge and analytical expertise, helping develop products that drive the business forward. 

We are looking for a problem-solver. You must be curious and focused on the future to excel in this position. A strong candidate will dive into new technologies, applying them to current needs while never losing sight of future innovations. 

The perfect candidate will push the boundaries of what’s possible while executing current long-term objectives. This position will work both on Brights Apps government AI work in addition to internal Bright Apps Projects. 

This data scientist will report to the CTO to brainstorm, present concepts, and work products, driving innovation forward. This position requires professionalism, understanding and the ability to deliver information clearly and concisely. The perfect candidate will feel comfortable presenting projects to diverse audiences while also taking constructive feedback and have a willingness to collaborate. 

Duties and Responsibilities

  • Design, train, hypertune, and deploy machine learning/deep learning algorithms and create frameworks to implement the models in real world applications 
  • Understand AI subsets, machine/deep/federated learning and NLP, and when to use which for a given problem ● Analyze and rank algorithms for best fit of a given problem and its metrics to be optimized 
  • Understand business objectives and develop models that help to achieve them, along with metrics to track their progress 
  • Explore and visualize data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world 
  • Handle large sets of data and implement techniques to aide in data privacy and security 
  • Conduct experimental designs to drive new hypotheses for new innovation trials 
  • Collect publicly available data for training 
  • Verify data quality and quantity, and/or ensuring it via data cleaning/pre-processing 
  • Ensure fairness and identify biases that may exist in a dataset and in a real world problem 
  • Design methods to combat data biases and ethics in AI
  • Use appropriate sensors to collect data from a physical environment to solve a given problem and then process signals/data with machine/deep learning algorithms and statistical methods
  • Design systems and circuits for wireless/radio communication Work hands-on with and understand microelectronics, soldering needed components in a system and testing for electrical errors
  • Explore and implement innovative methods of wireless communication and edge computing Define validation strategies 
  • Define augmentation and ML pipelines 
  • Utilize mathematical and visualization methods to analyze models, design strategies to overcome any errors, and present the results to others 
  • Evangelize and educate data sciences and the teams’ products throughout the business through effective communication and simple to understand use cases 
  • Aide in writing proposals and project descriptions 

Qualifications

  •  Competent using data science tools, libraries, and frameworks (NLP, Scikit-learn, NumPy, SciPy, Pandas, TensorFlow, PyTorch, Pandas, doc2vec, word2vec, general clustering and vector math)

  • Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress 

  • Managing available resources such as hardware, data, and personnel so that deadlines are met 
  • Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probability 
  • Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world 
  • Verifying data quality, and/or ensuring it via data cleaning 
  • Collect & monitor the data acquisition process if more data is needed 
  • Finding available datasets online that could be used for training 
  • Defining validation strategies 
  • Defining the preprocessing or feature engineering to be done on a given dataset 
  • Defining data augmentation pipelines
  • Training models and tuning their hyperparameters
  • Analyzing the errors of the model and designing strategies to overcome them 
  • Deploying models to production 
  • Competent with computer vision via PyTorch and OpenCV via Python 

1-2 years experience in Data Science, research and implementation
2-3 years of production level ML experience
Preferred advanced degree in Data Sciences / Computer Sciences or other STEM field.

Rate $120,000 - $180,000 Annual 

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Working Conditions

This position is 40 hours minimum, hourly, remote position. Will require ability to work independently

** Applicants residing outside of California, Oregon or Indiana this will be a contract 1099 position. Working conditions

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