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: • 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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