Job Description

Senior Data Specialist

Job requirements

• 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
• 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
• 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
• Bachelor's 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)