Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Dallas, TX, United States
Posted
2 weeks ago
DockerSQLAWSMLOpsMLflowMachine LearningNLPNumPyScikit-learnSnowflakeTableauAzureBigQueryComputer VisionDatabricksGenerative AIGitGoogle CloudKubernetesPandasPower BIPyTorchPythonRESTTensorFlow
Job Description
Data Scientist
Introduction
We are seeking an experienced Data Scientist to analyze complex datasets, develop predictive models, and deliver data-driven insights that support business and technical decisions. The ideal candidate will have strong experience in Python, SQL, machine learning, statistics, data visualization, and cloud platforms.
Responsibilities
- Analyze large and complex datasets to identify trends, patterns, and business opportunities.
- Develop, train, validate, and deploy machine learning and statistical models.
- Build predictive, classification, clustering, and recommendation models.
- Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis (EDA).
- Develop and optimize machine learning algorithms using Python and relevant frameworks.
- Work with structured and unstructured data from multiple sources.
- Create dashboards, reports, and visualizations to communicate analytical findings.
- Collaborate with Data Engineers, Software Engineers, Product Managers, and business stakeholders.
- Evaluate model performance using appropriate statistical and machine learning metrics.
- Implement model monitoring, validation, and continuous improvement processes.
- Work with cloud-based data and machine learning platforms.
- Document models, methodologies, assumptions, and analytical results.
- Stay current with emerging developments in AI, Machine Learning, Generative AI, and Data Science.
Requirements
Required Skills
- 5+ years of experience in Data Science, Machine Learning, Statistics, or a related field.
- Strong programming experience with Python.
- Strong SQL skills and experience working with relational databases.
- Experience with Machine Learning and statistical modeling.
- Experience with Pandas, NumPy, Scikit-learn and related Python libraries.
- Experience with data visualization tools such as Power BI, Tableau, Matplotlib, or Seaborn.
- Strong knowledge of statistics, probability, regression, classification, clustering, and hypothesis testing.
- Experience with data preprocessing, feature engineering, model evaluation, and optimization.
- Experience working with large datasets and distributed data environments.
- Strong analytical and problem-solving skills.
Preferred Skills
- Experience with PyTorch or TensorFlow.
- Experience with Spark / PySpark.
- Experience with AWS, Azure, or Google Cloud Platform.
- Experience with Databricks, Snowflake, or BigQuery.
- Knowledge of MLOps and model deployment.
- Experience with MLflow, Docker, Kubernetes, or CI/CD.
- Experience with Generative AI, LLMs, NLP, or Computer Vision.
- Experience with REST APIs and deploying machine learning models into production.
- Experience with Git/GitHub/GitLab.
Education
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
Typical Technology Stack
Python | SQL | Pandas | NumPy | Scikit-learn | TensorFlow/PyTorch | Spark/PySpark | MLflow | AWS/Azure/Google Cloud Platform | Databricks | Snowflake | Power BI/Tableau | Git
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