Roles & responsibilities :
Delivery of Key Projects:
- Successfully deliver advanced analytics and data science projects within predefined timelines and budget constraints.
Collaboration:
- Collaborate effectively with data engineers and ML engineers to comprehend data and models, utilizing various advanced analytics capabilities.
Solution Development:
- Develop efficient solutions for complex problems, showcasing expertise in data structures like Delta/Parquet, databases, data analytics, Python programming, and statistics.
End-to-End Pipeline Management:
- Manage the entire data science pipeline, including problem scoping, data gathering, modeling, insights generation, visualizations, monitoring, and maintenance.
Dashboard Design:
- Design dashboards using Python Dash (plotly) or Flask framework for effective data visualization and reporting.
Technological Expertise:
- Utilize CI/CD tools, data pipeline technologies, and visualization/data storytelling tools proficiently.
ETL Pipeline Building:
- Construct ETL pipelines using Python or Azure Synapse to facilitate efficient data processing and management.
Data Procurement and Management:
- Independently procure and process data, ensuring seamless integration within the company's overall data management strategy.
Technology Exploration:
- Continuously monitor advancements in artificial intelligence technology and identify applications for problem-solving within the company.
Technical Skills:
- Proficiency in Python and common libraries ( Dash, Pandas, Scikit-Learn, Pydantic, TensorFlow ).
- Strong knowledge of statistics and Probability .
- Set up cloud alerts, monitors, dashboards, and logging systems; troubleshoot data platform infrastructure as needed.
- Experience in OpenShift/Kubernetes and Azure ML is desirable.
- Proficiency in programming languages: Python (Dash) and database query languages SQL or KQL .
- Good applied statistical skills, including hands-on experience in time series modeling, predictive modeling, distributions, and
- regression .
- Knowledge of DevOps/MLOps .
- Exceptional analytical and problem-solving skills.
Preferred candidate profile
- Bachelor's or Master's degree in Computer Science or a related technical field, or equivalent experience.
- Total of 4 to 8 years of professional experience.
- Minimum of 4 years of experience in data science/machine learning .
- Minimum 3 years of experience with SQL .
- Experience in DevOps, preferably with hands-on experience in one or more cloud service providers, with Azure preferred.