Principal Data Scientist

This is a fully remote position, open to applicants in New Jersey.

📋 Description

• Create and execute robust statistical models and machine learning algorithms for extensive data analysis and predictive insights.

• Oversee the complete development of data science initiatives, encompassing hypothesis testing, regression analysis, classification, and forecasting.

• Partner with cross-functional teams to establish business requirements, convert them into analytical solutions, and deliver measurable outcomes.

• Enhance and automate data pipelines utilizing Python, PySpark, and R, ensuring effective data processing and feature engineering.

• Design, validate, and sustain probabilistic graph models and sophisticated statistical computing frameworks.

• Leverage top-tier ML frameworks like TensorFlow, PyTorch, and Sci-Kit Learn to construct, train, and implement models.

• Set up stringent model evaluation and monitoring protocols using instruments such as Great Expectations and Evidently AI.

• Mentor and support junior data scientists, promoting technical excellence and ongoing learning within the team.

⛳️ Requirements

• 15 - 18 years of experience in advanced data science positions, with significant leadership in the design and deployment of statistical and machine learning solutions.

• Proficiency in hypothesis testing, including methodologies such as T-Test and Z-Test.

• Advanced skills in regression techniques (both linear and logistic).

• Strong programming capabilities in Python, PySpark, and R/R Studio.

• Practical experience with SAS and SPSS for statistical analysis and computing tasks.

• Comprehensive understanding of probabilistic graph models.

• Experience with forecasting techniques such as Exponential Smoothing, ARIMA, and ARIMAX.

• Familiarity with classification algorithms including Decision Trees and Support Vector Machines (SVM).

• Proficient in ML frameworks: TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet.

• Knowledge of distance metrics (Hamming, Euclidean, Manhattan).

• Working experience with Kubeflow and BentoML for model deployment and orchestration.

• Master’s or PhD degree in Data Science, Statistics, Computer Science, Mathematics, or a related discipline.

• Relevant certifications in machine learning, statistical analysis, or advanced data science.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible working hours and remote work options.

• Opportunities for professional development and continuous learning.

• Collaborative and inclusive work environment.