K20s - Kinetic Technologies
Location
Mumbai | India
Job description
*Responsibilities:*
1. *Data Analysis and Modeling:*
- Lead the development and implementation of advanced machine learning models and algorithms.
- Perform in-depth analysis on large and complex datasets to derive actionable insights.
2. *Collaboration and Leadership:*
- Collaborate with cross-functional teams to understand business requirements and provide data-driven solutions.
- Mentor junior team members and provide technical leadership in data science initiatives.
3. *Model Evaluation and Optimization:*
- Evaluate model performance, identify areas for improvement, and implement optimizations.
- Stay abreast of industry trends and incorporate best practices into the data science workflow.
4. *Data Visualization and Communication:*
- Present findings and insights to both technical and non-technical stakeholders.
- Develop intuitive data visualizations to effectively communicate complex concepts.
5. *Data Quality and Governance:*
- Ensure data quality and integrity throughout the data science process.
- Adhere to data governance policies and industry standards.
*Additional Requirements:*
6. *Project Management:*
- Oversee end-to-end data science projects, ensuring timely delivery and meeting business objectives.
- Coordinate with project stakeholders and prioritize tasks to meet project timelines.
7. *Continuous Learning:*
- Stay updated on the latest advancements in data science and technology.
- Encourage a culture of continuous learning within the data science team.
8. *Collaborative Innovation:*
- Collaborate with other data scientists, analysts, and stakeholders to foster innovation and creative problem-solving.
*Qualifications:*
- Masters or Ph.D. in a quantitative field such as Computer Science, Statistics, or a related discipline.
- Proven experience as a Senior Data Scientist, demonstrating successful completion of complex data science projects.
- Expertise in machine learning, statistical modeling, and data analysis techniques.
- Proficiency in programming languages such as Python or R.
- Strong leadership and communication skills.
*Preferred Skills:*
- Experience with big data technologies (e.g., Hadoop, Spark).
- Knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch).
- Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud).
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