Senior Data Specialist R01571898

Experience Range: With at least 5 years of hands-on experience in advanced data science, including statistical analysis and machine learning, and up to 8 years in related roles Key Responsibilities:

Design and implement advanced statistical models, including hypothesis testing, regression analysis, and classification algorithms, to drive business outcomes

Conduct rigorous statistical analysis using t-tests, z-tests, and probabilistic graph models to extract actionable insights from large datasets

Build, train, and deploy predictive models for forecasting and classification tasks using machine learning frameworks such as TensorFlow, PyTorch, and Sci-Kit Learn

Perform data cleaning, transformation, and exploratory analysis utilizing Python, PySpark, R, and statistical tools like SAS or SPSS

Apply time series forecasting methods, including exponential smoothing, ARIMA, and ARIMAX, to predict trends and inform strategic decisions

Develop and maintain data validation and monitoring pipelines to ensure data quality and model performance

Collaborate with cross-functional teams to translate business requirements into analytical solutions and communicate findings effectively

Automate machine learning workflows to streamline deployment and enhance scalability

Required Skills:

Expertise in hypothesis testing (t-test, z-test)

Advanced regression analysis (linear and logistic)

Programming proficiency in Python and PySpark

Hands-on experience with SAS or SPSS for statistical computing

Knowledge of probabilistic graph models

Experience with data validation frameworks such as Great Expectations

Time series forecasting techniques (exponential smoothing, ARIMA, ARIMAX)

Familiarity with classification algorithms (decision trees, SVM)

Experience with machine learning frameworks (TensorFlow, PyTorch, Sci-Kit Learn)

Proficiency in R for statistical modeling

Preferred Skills:

Experience with distance metrics (Hamming, Euclidean, Manhattan)

Expertise in model monitoring tools beyond Great Expectations, such as Evidently AI

Experience in deploying models using BentoML

Familiarity with orchestration tools for ML workflows, such as KubeFlow

Background in designing scalable machine learning pipelines

Desired Qualifications:

Bachelors degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline

Certification in Data Science, Machine Learning, or Advanced Analytics (e.g., Microsoft Certified: Azure Data Scientist Associate, SAS Certified Data Scientist)

Certification in Python or R programming (e.g., PCEP, PCAP, R Programming Certification) .