Senior Data Scientist

Precision Inc.
Monmouth Junction, United States
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Job source

Tech stack

A/B Testing Artificial Intelligence Amazon Web Services Data Analysis Microsoft Azure Big Data Cloud Computing Cloud Database Cluster Analysis Continuous Integration Data Visualization Relational Databases
+39 more
Distributed Computing Environment Apache Hadoop Statistical Hypothesis Testing Python (Programming Language) Machine Learning Language Modeling Natural Language Processing NumPy Recommender Systems Power BI Tensorflow Azure Machine Learning Sentiment Analysis Software Deployment SQL Databases Tableau (Software) Feature Store Cloud Platform System Feature Engineering Data Ingestion Sql Optimization Pytorch Apache Spark Deep Learning Model Validation Pandas Matplotlib AI Platforms Pyspark Scikit Learn Kubernetes Xgboost Plotly Machine Learning Operations Drift Detection Text Analysis Data Pipelines Docker Unsupervised Learning

Job description

Job Summary: We are seeking a highly experienced Senior Data Scientist with 10+ years of experience in advanced analytics, statistical modeling, and machine learning solution development. The ideal candidate will design, develop, validate, and deploy scalable predictive and prescriptive models using modern data science, AI/ML, and cloud technologies. This role requires strong expertise in Python, statistical analysis, machine learning algorithms, big data platforms, cloud ecosystems, MLOps practices, and business-driven analytics delivery., * Design, develop, and deploy machine learning and deep learning models for predictive analytics, classification, regression, clustering, recommendation systems, and forecasting.

  • Build end-to-end data science pipelines including data ingestion, feature engineering, model training, validation, and production deployment.
  • Develop advanced analytics solutions using Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM).
  • Perform exploratory data analysis (EDA) and statistical hypothesis testing using statistical techniques and probability modeling.
  • Work extensively with SQL and RDBMS platforms to extract, transform, and analyze large datasets.
  • Process and analyze large-scale datasets using big data technologies such as Spark, PySpark, or Hadoop ecosystems.
  • Develop Natural Language Processing (NLP) models for text analytics, sentiment analysis, and language modeling where applicable.
  • Implement model validation techniques, cross-validation, A/B testing, and performance evaluation metrics (ROC-AUC, precision-recall, RMSE, etc.).
  • Deploy machine learning models into production using MLOps frameworks, CI/CD pipelines, Docker containers, and Kubernetes.
  • Leverage cloud platforms (Azure, AWS, or GCP) for scalable model training, deployment, and monitoring.
  • Develop and maintain automated model monitoring and drift detection frameworks.
  • Create interactive dashboards and visualizations using Power BI, Tableau, or Matplotlib/Seaborn/Plotly to communicate insights to stakeholders.
  • Collaborate with data engineers to optimize data pipelines and feature stores.
  • Translate complex analytical results into actionable business insights for executive and non-technical stakeholders.
  • Provide technical leadership, mentor junior data scientists, and contribute to enterprise AI strategy initiatives.

Requirements

  • Advanced proficiency in Python for data science and machine learning development.
  • Strong expertise in Machine Learning algorithms, supervised and unsupervised learning techniques.
  • Experience with Deep Learning frameworks such as TensorFlow or PyTorch.
  • Strong foundation in Statistics, Probability, Linear Algebra, and Predictive Modeling.
  • Advanced SQL skills and experience working with enterprise RDBMS systems.
  • Experience with Big Data platforms such as Spark or distributed computing frameworks.
  • Hands-on experience deploying models using Docker, Kubernetes, and MLOps best practices.
  • Experience working with cloud-based data science platforms (Azure ML, AWS SageMaker, or GCP AI Platform).
  • Strong experience in data visualization and storytelling using BI tools.
  • Experience working in Agile/Scrum environments and cross-functional teams.

About the company

About Precision Technologies

201-500 Monmouth Junction, New Jersey, United States Website

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