Sr. Data Scientist

Lorven Technologies Inc

Boston, MA, United States

26 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Compensation

$41,600.0 - $83,200.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Artificial Intelligence Data Analysis Microsoft Azure Big Data Cluster Analysis Data Mining Data Visualization Distributed Systems R (Programming Language) Statistical Hypothesis Testing Python (Programming Language) Machine Learning

+25 more

Object-Oriented Software Development Performance Tuning Scrum Methodology Power BI Azure Machine Learning Software Construction SQL Databases Tableau (Software) Unstructured Data Management of Software Versions Enterprise Software Applications Feature Engineering Azure Data Factory Apache Spark Model Validation Git Matplotlib Pyspark Information Technology Plotly Machine Learning Operations Azure Synapse Analytics Software Version Control Data Pipelines Databricks

Job description

Design, develop, and deploy scalable Machine Learning and statistical models to solve complex business problems.
Build reusable and production-ready data science solutions using Python, R, Azure Databricks, and Azure Machine Learning.
Perform exploratory data analysis (EDA), feature engineering, model selection, training, validation, and optimization.
Collaborate with Data Engineers to build scalable data pipelines and prepare datasets for machine learning applications.
Analyze large-scale structured and unstructured datasets to generate actionable business insights and recommendations.
Develop predictive, classification, clustering, recommendation, and forecasting models based on business requirements.
Deploy, monitor, and maintain machine learning models in Azure cloud environments while ensuring model performance and reliability., Role Overview As a Computer Science Specialist, you will leverage your advanced expertise to support projects that train next-generation AI systems. Your contributions will direc…
4 days ago, Job Description: ABOUT POWER FACTORS Power Factors is a leading software and solutions provider supporting the next generation of clean energy through Unity, one of the most co…
15 hours ago +

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Artificial Intelligence, Machine Learning, or a related field with an overall of 12+ years of IT experience.
Strong hands-on experience in Python and R for data analysis, statistical modeling, and machine learning solution development.
Extensive experience designing, building, and deploying Machine Learning (ML) models for predictive and prescriptive analytics.
Strong experience working with Azure Cloud, including Azure Machine Learning, Azure Databricks, Azure Storage, Azure Data Factory, Azure Synapse Analytics, and related Azure services.
Hands-on experience with Azure Databricks for large-scale data processing, feature engineering, model training, and distributed computing using Spark/PySpark.
Strong understanding of statistical techniques including regression, classification, clustering, forecasting, hypothesis testing, and model evaluation.
Experience developing scalable and reusable data science solutions that can be integrated into enterprise applications.
Strong proficiency in SQL for data extraction, transformation, querying, and performance optimization.
Experience working with structured and unstructured datasets from multiple enterprise data sources.
Familiarity with MLOps concepts including model deployment, versioning, monitoring, and lifecycle management.
Experience with data visualization tools such as Power BI, Tableau, Matplotlib, or Plotly to communicate analytical insights.
Experience using Git for source code management and collaborative development.
Strong understanding of software engineering best practices, object-oriented programming, and data science lifecycle methodologies.
Experience working in Agile/SCRUM environments with cross-functional teams including Data Engineers, Software Engineers, Product Owners, and Business Stakeholders.
Excellent analytical, problem-solving, communication, and stakeholder management skills.