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Protocol Intelligence
Data-driven signals on your job's competitivenessMid-level generalist ML role, metro location, and broad technical requirements increase applicant competition.
Core ML and statistics skills transfer across industries, but specific tools and deployment experience increase domain specificity.
Many mandatory technical skills, explicit 4+ years requirement, and deployment experience tighten shortlisting.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and deploy advanced statistical and machine learning models to solve complex business problems.
Conduct rigorous statistical analysis and implement data quality checks to ensure integrity of data and models.
Collaborate with cross-functional teams to translate business requirements into analytical solutions and maintain forecasting and classification models in production.
Minimum Requirements
Minimum 4 years of experience in advanced data science, statistical analysis, and machine learning model development, including production deployment.
Proficiency in Python, PySpark, and statistical tools such as SAS or SPSS.
Experience with regression, classification algorithms, forecasting techniques (exponential smoothing, ARIMA, ARIMAX), and data validation tools like Great Expectations and Evidently AI.
Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related field.
Ideal Candidate Profile
Strong expertise in production-level model deployment using cloud-native tools like KubeFlow or BentoML and familiarity with cloud analytics platforms (AWS SageMaker, Azure ML, Google AI Platform).
Proficient in advanced ML frameworks including TensorFlow, PyTorch, and Keras with experience in deep learning.
Skilled in both statistical and machine learning methodologies, capable of bridging rigorous analysis with scalable production implementation.