Andiamo is a globally recognized staffing and consulting firm specializing in placing top technology professionals. The role of Senior Data Scientist involves developing advanced analytical models and algorithms to transform complex datasets into actionable insights, while collaborating with technical teams and business stakeholders.
Responsibilities:
- Design and implement statistical and machine learning models to solve complex business problems, including classification, regression, anomaly detection, and forecasting
- Analyze large datasets to identify patterns, relationships, and anomalies. Perform data cleaning, transformation, and feature engineering to prepare data for modeling
- Develop and refine algorithms using advanced statistical techniques and machine learning methodologies to improve model accuracy and performance
- Build and deploy analytical solutions using modern tools and frameworks, ensuring scalability, reliability, and maintainability in production environments
- Partner with domain experts, engineers, and architects to align data models with business objectives and technical infrastructure
- Work with technical teams to ensure appropriate data flow, storage, and processing architectures support analytical workloads
- Validate models using statistical testing and performance metrics. Monitor models over time to ensure continued accuracy and relevance
- Translate complex analytical findings into clear, actionable insights for both technical and non-technical stakeholders
- Support team development by sharing expertise, guiding less experienced team members, and contributing to a collaborative learning environment
Requirements:
- Bachelor's or Master's degree in Data Science, Computer Science, Information Technology, Statistics, or a related field. Equivalent experience may also be considered
- Strong proficiency in Python and SQL for data analysis, model development, and data manipulation
- Hands-on experience working with Databricks in production environments (required)
- Experience developing and deploying predictive models and analytical solutions in real-world applications
- Strong understanding of statistical methods including hypothesis testing, regression analysis, probability distributions, and time series modeling
- Experience working with large-scale datasets and distributed computing environments, including cloud platforms such as AWS or Azure
- Ability to analyze complex systems, identify root causes, and develop data-driven solutions
- Strong ability to communicate technical concepts and analytical findings clearly to diverse audiences
- Experience working with the Ray framework for distributed computing
- Familiarity with big data tools and open-source ecosystems
- Experience in Agile development environments
- Knowledge of CI/CD pipelines and model deployment best practices
- Experience validating and testing machine learning systems in production
- Exposure to reliability engineering or system performance domains