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 effective 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.

📌 Data Marketing Scientist (Bengaluru)
🏢 Lufthansa Technik Services India
📍 Bengaluru