Senior Data Scientist

We are looking for a skilled and passionate Data Scientist to join our team. The ideal candidate will have 5-8 years of experience in leveraging data to generate actionable insights, build predictive models, and apply machine learning techniques to solve complex business problems. The role requires expertise in Python, Cloud technologies (preferably Azure), and experience in deploying and maintaining productionized machine learning models.

Key Responsibilities:

1. Data Exploration & Analysis:

   • Perform exploratory data analysis (EDA) to identify patterns, trends, and relationships in large datasets.
   • Analyze data to extract actionable insights and create data visualizations to communicate findings effectively to stakeholders.

2. Model Development:

   • Build, train, and deploy machine learning models for predictive analysis, recommendation systems, or classification tasks.
   • Develop models using advanced techniques, including regression, classification, clustering, and time-series forecasting.
   • Use appropriate algorithms and methodologies to address business problems and improve performance.

3. Model Productionization:

   • Work with engineering and DevOps teams to deploy machine learning models into production environments.
   • Ensure the models are scalable, reliable, and optimized for performance.
   • Monitor model performance in production and apply necessary updates to improve accuracy and efficiency.

4. Cloud/Platform Integration:

   • Utilize Azure or other cloud platforms to manage data, models, and applications.
   • Collaborate with cloud engineering teams to ensure proper integration and seamless deployment of data science solutions.

5. Collaboration with Cross-functional Teams:

   • Collaborate with business analysts, product managers, and other teams to define business problems and model requirements.
   • Communicate technical insights and results to non-technical stakeholders in a clear and actionable way.

6. Research and Innovation:

   • Stay updated with the latest developments in data science, machine learning, and AI.
   • Experiment with new algorithms, libraries, and techniques to improve model accuracy and efficiency.

7. Documentation & Reporting:

   • Document methodologies, processes, and results for reproducibility and knowledge sharing within the team.
   • Prepare reports and presentations for management and business stakeholders.

Required Skills and Qualifications:

• 5-8 years of experience in Data Science or related fields.
• Proficiency in Python and machine learning libraries such as Pandas, Scikit-learn, TensorFlow, Keras, or PyTorch.
• Experience with Azure or other cloud platforms, including handling cloud-based machine learning workflows.
• Hands-on experience in deploying and maintaining productionized predictive models.
• Strong experience in Exploratory Data Analysis (EDA), data wrangling, and feature engineering.
• Solid understanding of machine learning algorithms and their applications in real-world business problems.
• Ability to work with large datasets and understand database management systems (SQL, NoSQL).
• Strong communication skills and ability to present complex data science concepts to non-technical stakeholders.
• Bachelor s or Master s degree in Computer Science, Data Science, Mathematics, or a related field.

Preferred Skills:

• Knowledge of big data tools such as Hadoop, Spark, or similar.
• Experience with MLOps tools and frameworks for managing machine learning pipelines.
• Exposure to Deep Learning and advanced AI techniques.