Senior Data Specialist
Job requirements
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:
- 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)
Additional Information: Immediate joiner required
