Principal Data Science
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:
Bachelors or masters 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
Apply Now
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:
Bachelors or masters 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
Apply Now