Overview
Remote
Hybrid
Depends on Experience
Contract - Independent
Contract - W2
Contract - 12 Month(s)
Skills
Senior Data Scientist
Job Details
Job Summary:
We are seeking a highly experienced and results-driven Senior Data Scientist with a minimum of 12 years of relevant industry experience. The ideal candidate will have a strong foundation in data analytics, statistical modeling, machine learning, and big data technologies. This role requires deep technical expertise and the ability to lead complex projects that drive business innovation and strategic insights.
Key Responsibilities:
- Lead end-to-end data science projects from problem formulation and data acquisition to model deployment and performance monitoring.
- Design and implement predictive models, machine learning algorithms, and statistical analyses to solve complex business problems.
- Collaborate with cross-functional teams including data engineering, product, and business stakeholders to translate requirements into data-driven solutions.
- Conduct exploratory data analysis and generate actionable insights from large and complex datasets.
- Develop reusable code libraries and best practices for model development and deployment.
- Mentor junior data scientists and guide the team in adopting new technologies and techniques.
- Stay current with advancements in data science, machine learning, and AI research.
Required Qualifications:
- Bachelor s degree or higher in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
- Minimum 12 years of relevant experience in data science, analytics, or a similar role.
- Proven track record of delivering impactful machine learning and data-driven solutions in a production environment.
Technology Stack & Skills:
- Programming Languages: Python, R, SQL
- Machine Learning & Statistical Tools: scikit-learn, XGBoost, TensorFlow, PyTorch, Anthropic Claude, stats models
- Data Manipulation & Analysis: Pandas, NumPy, Spark
- Visualization Tools: Matplotlib, Seaborn, Plotly, Tableau, Power BI
- Big Data & Cloud Platforms: Hadoop, Hive, AWS (S3, SageMaker, Redshift), Azure, or Google Cloud Platform
- Version Control & Collaboration: Git, Jupyter, Docker
Preferred Qualifications:
- Master s or Ph.D. in a quantitative field is a plus.
- Experience with MLOps, model monitoring, and deployment pipelines.
- Familiarity with NLP, computer vision, or deep learning techniques.
Domain expertise in [e.g., finance, healthcare, retail, etc.] is advantageous
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