Principal Data Science
3 months ago
**Role: Principal Data Science Engineer**
**Exp: 10+ Years**
**Location: Remote**
**Notice Period: 30 Days Max**
**Key Responsibilities**:
- **Model Development and Implementation**:
- Design, develop, and deploy advanced data science models and algorithms.
- Ensure models are scalable, maintainable, and optimized for performance.
- **Leadership and Mentorship**:
- Lead and mentor a team of data scientists and engineers, providing technical guidance and support.
- Foster a culture of continuous learning and innovation within the team.
- **Collaboration**:
- Work closely with product managers, engineers, and business stakeholders to understand data requirements and deliver solutions.
- Collaborate with data engineering teams to ensure seamless integration of data science models into production systems.
- **Research and Innovation**:
- Stay current with the latest advancements in data science and machine learning.
- Evaluate and implement new tools, techniques, and technologies to enhance our data science capabilities.
- **Data Analysis and Insight Generation**:
- Conduct exploratory data analysis to uncover trends, patterns, and insights.
- Translate complex data into actionable insights and recommendations for business stakeholders.
- **Project Management**:
- Lead data science projects from conception to completion, ensuring timely delivery and high-quality results.
- Develop project plans, timelines, and resource allocation.
**Qualifications**:
- **Education and Experience**:
- Bachelor’s or master’s degree in computer science, Statistics, Mathematics, or a related field.
- 10+ years of experience in data science, with a proven track record of developing and deploying advanced models.
- **Technical Skills**:
- **Experience with Databricks**:
- Proficiency in programming languages - Python, Pyspark.
- Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong knowledge of statistical analysis, data mining, and predictive modelling. Machine learning algorithms (supervised/unsupervised/deep learning). Model evaluations & validation.
- Experience with big data technologies (e.g., Hadoop, Spark)
- Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and their data services. AWS knowledge is must.
- Docker, Kubernetes
- Any DB experience, SQL query writing and optimization
- Soft Skills:
- **Excellent problem-solving and analytical skills.**:
- Strong communication and interpersonal skills.
- Ability to work effectively in a fast-paced, dynamic environment.
**Job Type**: Permanent
Pay: ₹3,000,000.00 - ₹5,000,000.00 per year
**Experience**:
- total work: 10 years (required)
- Machine Learning Frameworks: 3 years (required)
- Machine learning algorithms: 3 years (required)
- Big Data Technologies: 2 years (required)
- Cloud Platforms (e.g., AWS, GCP, Azure): 2 years (required)
- AWS: 1 year (required)
- Docker/Kubernetes: 3 years (required)
- Database: 3 years (required)
- Python: 2 years (required)
- Pyspark: 2 years (required)
Work Location: Remote
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