Machine Learning Engineering Manager
Employment Type: Full-Time
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Mitchell & Genex have Merged
Mitchell is a trusted software and service provider to the Property & Casualty Claims and collision repair industries as well as risk management professionals. We provide technology and services that simplify claims handling, repair processes and pharmacy transactions with best in class clinical management and cost containment solutions. Genex helps injured workers return to their jobs in a safe and efficient manner through compassionate case management, reducing health care costs and disability expenses for our customers.
Together, we bring two industry leaders in software and service committed to delivering a first-class experience to the customers, partners and markets we serve. We offer a complete suite of technology enabled solutions, and a proven managed care service mix, allowing us to deliver better outcomes to our clients for their businesses, their employees and their customers.
We are looking for a Machine Learning Engineering Manager having insatiable intellectual curiosity and passion about developing intelligent products and applying Computer Vision; Artificial Intelligence (Deep learning) and Machine learning techniques to solve real business problems in the P&C sector.
As a ML Engineering Manager, Your primary focus will be to apply your experience in managing teams and Machine Learning knowledge in developing 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 and apply them to vast amounts of data. 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
- Leading engineering projects and a team of data scientists from inception to shipped software.
- 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,
- Working collaboratively in coming up with strategy around labelling vast amounts of images 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 expertise when needed to mitigate risk.
You must have
- Consistent track record of hiring, managing, and developing great Data Scientists and Engineers.
- Deep & broad understanding of machine learning theory, practice, and tools.
- Passionate problem solver, building the best solutions for the most important problems.
- Ability to communicate thoughtfully, leveraging problem-solving skills and a learning mindset to build long-term relationships.
- At least 5+ years hands-on software development experience and applied machine learning experience.
- At least 3+ years of engineering management experience.
- At a Minimum - Master s Degree in Computer Science, Data Science, Mathematics or related field
- Sound coding knowledge of scientific, distributed programming and scripting languages like Python, PyTorch, PySpark and/or Java.
- Solid foundation in statistics, machine learning, data structures, algorithms, and software design.
- Excellent understanding of machine learning, AI techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Ensembles, Decisions Trees, and CNNs.
- Experience with common data science toolkits, such as Scikit-learn, MLLib, Google Inception, Google TensorFlow, Weka, NumPy, SciPy, MatLab, Excellence in at least three of these is highly desirable.
- Proficiency in using query languages such as SQL, PL/SQL.
- 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 cloud framework like AWS SageMaker, GCP MLE as well as data visualization tools, such as D3.js, Tableau, Kibana, GGplot is a plus.
- Familiarity of modern statistical learning methods & machine learning Frameworks like H2O, Spark, and PyTorch
- Experience working with cloud infrastructure like AWS, Azure and/or GCP.
- Experience with NoSQL databases, such as MongoDB, HBase is a plus
Mitchell International, an equal opportunity employer, values the diversity of our workforce and the knowledge of our people. Mitchell will not discriminate against an applicant or employee on the basis of race, color, religion, national origin, ancestry, sex/gender, age, physical or mental disability, military or veteran status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other characteristic protected by applicable federal, state or local law.
Associated topics: chief program officer, cpo, manage, manager, management, monitor, product manager, project manager, relationship manager, task
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