Mitchell International, Inc.

Sr. Machine Learning Engineer

US-CA-San Diego
Job ID
16-7196
Type
Regular Hire

Company Overview

Mitchell International, Inc. is a leading provider of information and workflow solutions to the Property & Casualty Claims Industry and their supply chain partners. We solve interesting and complex problems that directly affect the customers our clients serve. We are constantly adapting to stay on the forefront of emerging technologies and we work diligently to maintain our position as a thought leader within our industry.

 

At Mitchell, we are building next generation suite of smart product solutions using Advanced Analytics and Artificial Intelligence.

Job Description

We are looking for a Sr. Machine Learning Engineer with insatiable intellectual curiosity and a passion for developing intelligent products. This person will be eager to apply Artificial Intelligence (Deep learning) and Machine learning techniques to solve real business problems.

 

As a ML Engineer, Your primary focus will be to apply your Machine Learning knowledge by creating algorithmic solutions that combine techniques like clustering, Image based pattern mining, predictive modeling, deep learning, statistical Analysis, information retrieval, computer vision and natural language processing. You will help us analyze and discover information hidden in the vast amounts of data (Textual as well as Image), and help us make smarter decisions and deliver AI enabled products to our customers. 

 

You will be responsible to solve many challenging problems, including

  • Building models at scale using vast amounts of structured and unstructured heterogeneous types of data.
  • Ensuring high accuracy based on industry’s stringent requirements around precision or recall and with minimum Type I and Type II errors.
  • Generating predictions for millions of rows of data with high response time
  • Dealing with high data diversity (vast amounts of data will need to be classified and will have multi labelled outcomes)
  • Dealing with very high dimensionality (expect to work on large matrix computations, variable transformation & feature engineering and selection using PCA and other novel ML techniques)
  • Dealing with noisy data (build models robust enough for unclassified and/or mislabeled data)

You will primarily work on

  • Coming up with labelling vast amounts of Image as well as Textual data
  • Applying ML techniques like collaborative filtering, bootstrap aggregation (bagging), Random Forest and Ensemble algorithms and generate statistically significant models.
  • Selecting features, building and optimizing classifiers using machine learning techniques
  • Data mining using state-of-the-art methods
  • Extending company’s data with third party sources of information when needed.
  • Enhancing data collection procedures to include information that is relevant for building analytic systems
  • Processing, cleansing, and verifying the integrity of data used for analysis
  • Doing ad-hoc analysis and presenting results in a clear manner
  • Creating automated anomaly detection systems and constant tracking of its performance
  • Being creative and going far beyond theoretical solutions to deal with challenges outlined.
  • Meeting business requirements with domain knowledge into complex data analytical workflows and efficiently utilize experts when needed to mitigate risk. 

 

Qualifications

Must have

  • 3+ years applied machine learning experience.
  • Minimum - Master’s Degree in Computer Science, Data Science, Mathematics or related field 
  • Sound coding knowledge of scientific, distributed programming and scripting languages like R, Python, PySpark and/or Java.
  • Solid foundation in statistics, machine learning, data structures, algorithms, and software design.
  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Ensembles, Decisions Trees.
  • Experience with common data science toolkits, such as Scikit-learn, MLLib, Google  inception, Google tensorflow, R, Weka, NumPy, SciPy, MatLab, Excellence in at least three of these is highly desirable.
  • Proficiency in using query languages such as SQL, PL/SQL, Hive, Pig or PostgreSQL.
  • Experience Big Data framework like Hadoop
  • Good applied statistics skills, such as distributions, statistical analysis and testing (T Test), and regression techniques
  • Great communication skills and Data-oriented personality
  • Experience with data visualization tools, such as D3.js, Tableau. Kibana, GGplot is a plus.

 

Preferred Qualifications

  • Familiarity of modern statistical learning methods & machine learning Frameworks like H2O, Spark
  • Experience working with cloud infrastructure like AWS, Azure and/or Openstack
  • Experience with NoSQL databases, such as MongoDB, HBase is a plus
  • Experience with elastic search is a plus
  • Access to Github repository

 

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