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Machine Learning Engineer

Machine Learning Engineer
Soothsayer Analytics is seeking Machine Learning Engineer who has an interest in solving challenging ML/ AI problems in Insurance. Our AI team works on a variety of exciting analytics (ML, AI) projects.

Number of positions: 4
Immediate need, need someone to start within 1-2 weeks max.

Required Education:
  • PhD in computer science, Physics, Statistics, Applied Mathematics, or other quantitative/ Computational discipline or Master's with over 5 years of real-time relevant real-time Industry experience as an AI/ML/ Deep Learning is a MUST.
Required experience: At least 5 years of industry experience as a Data Scientist is required.
Job Description:
  • Participate in requirements gathering, technical specification, design, and development of complex operationalizing machine learning projects.
  • Ability to translate business requirements into plausible technical solutions for the articulation to other development team members.
  • Contribute to the architecture design, development of data or machine learning pipelines, and integration into enterprise systems
  • Responsible for Build and configure multi-tenant machine learning environments on-prem, cloud, or hybrid
  • Responsible for Build, test and optimize AI/ML models
  • Interact with teams of engineers from multiple disciplines Identifying and defining the scope
  • Defining technical approach, data and algorithms needed
  • Responsible for building out the data product from POC to product
  • Communicate modeling results and its business impact to scientific and business stakeholders
  • Collaborate with other engineers, data scientists, and business analysts.
Machine Learning Engineer/ Data Scientist
  • Advanced level Experience in Python and ML
  • Experience with building Machine Learning models and pipelines using tools like Python and Spark in AWS SageMaker.
  • Experience building a variety of deep learning methods (autoencoders, embeddings etc.) using Pytorch, Tensorflow.
  • Experience building time series models
  • Proficient in data processing using pandas and pySpark. Ad hoc analysis to describe and understand data sets.
  • Familiarity with MLOps
  • Knowledge of SQL for accessing and processing data
  • Experience with at least one CI/CD tool, e.g. Jenkins, Github actions, or cloud equivalents
  • Experience in hyperparameter tuning, model selection and metrics. The candidate should demonstrate the ability to be well organized and perform error analysis to investigate model performance.
  • Experience building visualizations using python.
  • Hands on experience in a range of ML and AI techniques (e.g. supervised and unsupervised machine learning techniques, deep learning)
  • Deep understanding of data manipulation/wrangling techniques
Required Skills/ Skills Matrix:
  • Data Analysis and Modeling using Python/Spark – 5 years = Must
  • Distributed data processing using pyspark - 3 years = Must
  • Deep Learning on structured data - 3 years = Must
  • Computer Vision/NLP - 12 months = Good to have
  • MLOps - 6 months = Must
  • Time Series Analysis and Modeling – 1 year = Must
  • Domain experience in solving ML problems in one or more of Insurance - 3 years = Must
  • AWS SageMaker – 1 year - Must

Covid-19 update: Work from our office in Detroit, MI, remote work is not allowed.
About Soothsayer Analytics
Soothsayer Analytics is a Data Science company based out of Livonia, MI and offices in Columbus, OH and offshore in Hyderabad India. Advanced Analytics firm focused on Pattern Recognition and Unstructured Data. Our team actively works with, creates, and researches cutting edge Data Science techniques. We approach each problem individually and architect custom solutions. Our strength lies in our ability to build and productize proprietary algorithms and analytical tools. Advised by 10 industry experts whose domain knowledge we leverage to better architect industry specific solutions. Our delivery partners include 20+ Data Scientists with a combined 75 Patents and 300+ Publications. We collaborate with this brain trust to keep us abreast of state-of-the-art techniques and to help deliver world-class results. We utilize cutting edge Machine Learning and Statistical Techniques to extract Hidden Insights and Patterns from Complex, High Dimensional, and Unstructured Data. Our major clients include: DOW Chemicals, Ford, Visteon, D&B, Timken, US steels, Steelcase, Abercrombie, Express, Stanley Steemer, Whirlpool, AEP, NiSource, GEA, etc.

Soothsayer Analytics is an Equal Opportunity Employer and e-Verify Company.