Data Scientist

Job Title: Data Scientist

strong combination of technical expertise, leadership skills, and business acumen

Responsibilities:

• Lead, mentor, and inspire a team of junior data scientists, fostering a collaborative and innovative work environment.
• Provide technical guidance, set priorities, and ensure the team's alignment with organizational goals.
• Conduct regular performance assessments and contribute to professional development plans.
  

Strategy and Planning:

• Collaborate with stakeholders to understand business objectives and identify opportunities for leveraging data to achieve strategic goals.
• Develop and execute a data science roadmap, ensuring alignment with overall business and technology strategies.
• Stay abreast of industry trends, emerging technologies, and best practices in data science.
  

Advanced Analytics:

• Design, develop, and implement advanced machine learning models and algorithms to extract insights and solve complex business problems.
• Drive the exploration and application of new data sources, tools, and techniques to enhance analytical capabilities.
• Collaborate with data engineers to ensure the scalability and efficiency of deployed models.
  

Cross-functional Collaboration:

• Collaborate with cross-functional teams, including business analysts, software engineers, and domain experts, to integrate data science solutions into business processes.
• Communicate complex analytical findings to non-technical stakeholders in a clear and actionable manner.
  

Data Governance and Quality:

• Establish and enforce data governance standards to ensure the accuracy, reliability, and security of data used for analysis.
• Work with data engineering teams to enhance data quality and integrity throughout the data lifecycle.
  

Project Management:

• Oversee the end-to-end execution of data science projects, ensuring timelines, budgets, and deliverables are met.
• Provide regular project updates to stakeholders and manage expectations effectively.
  

Technical Expertise:

• Provide technical guidance and execution for the latest GenAI technologies, including but not limited to LLM/SLM/VLM and Multi-modal AI Algorithms. Leverage Transformers for complex natural language processing-based tasks.
• Lead the development of deep learning technologies like computer vision for image processing, OCR/IDP, object detection and tracking, segmentation, Image generation, Convvolutional Neural Networks, Capsule Networks, etc.
• Development of core Machine Learning algorithms like time series analysis with Neural ODEs; Variational Autoencoders for Image Generation and anomaly detection;
• Provide oversight for core deep learning algorithms like Neural Architecture Search for optimization and Graph Neural Networks for molecular structures.

Qualifications:

• Minimum 1+ years of experience leading a team of junior data scientists, with a proven track record of successful project implementations.
• Master's or Ph.D. in a quantitative field (Computer Science, Statistics, Mathematics, etc.)
• Experience with GenAI, Agentic AI, LLM Training, and LLM-driven workflow development. Knowledge of large multi-modal models is a must.
• Experience in MLOps, Scientific Machine Learning, Statistical Modeling, and Data Visualization.
• Must have experience with the development and implementation of various core Machine Learning algorithms mentioned above.
• Must have hands-on experience with Deep Learning technologies for computer vision and image processing as well as core neural network applications like optimization.
• Experience in developing ML, AI, and Data Science solutions and putting solutions in production, with proficiency in Data Engineering, is desirable.
• Experience in the development and implementation of scalable and efficient data pipelines using AWS services such as SageMaker, S3, Glue, and/or Redshift.
• Excellent leadership, communication, and interpersonal skills.

Experience with big data technologies and cloud platforms is a plus.