Data Scientist

We are looking for a proactive Data Scientist with strong AI/ML and Large Language Model (LLM) expertise, particularly in time-series modeling. The ideal candidate should have experience analyzing diverse datasets, building machine learning models, and deploying AI solutions for business value. Responsibilities include developing models from business data, with opportunities to work on deep learning, computer vision, natural language processing, LLMs, and multi-agent systems.

You will design, train, and deploy scalable AI/ML models and turn data insights into actionable strategies.

• Data Analysis & Feature Engineering:
  Collect, process, and analyze structured and unstructured data, engineering relevant features to improve model performance.
• Develop, train, and optimize machine learning and deep learning models for time-series analysis and anomaly detection.
• LLM and Agent-based Application:
  Build AI solutions using LLMs, emphasizing prompt engineering, multi-agent systems, fine-tuning, and inference optimization.
• Business Impact & Decision Support:
  Translate complex data science methodologies into actionable insights, collaborating with stakeholders to drive business value.
• Data Storytelling & Visualization:
  Develop clear, compelling presentations and dashboards to communicate findings to non-technical stakeholders.

• A solid foundation in time-series modeling and anomaly detection is required.
• Proficiency in Python and experience with time-series modeling techniques such as linear regression, random forest, and boosting are required.
• Strong communication abilities and a track record of collaborating with stakeholders and business owners are important.
• Deep learning, Generative AI, computer vision, data engineering, and ML Ops experience is helpful but not required.

• Curious & Innovative:
  Passionate about solving complex business problems using data and AI.
• Ownership & Initiative:
  Proactively drive projects from conception to deployment.
• Business Acumen:
  Understand how AI/ML solutions impact business goals and decision-making.
• Effective Communication:
  Ability to explain technical models and AI methodologies to non-technical audiences.

• Graduate degree (Master’s or Ph.D.) in a quantitative field (e.g., Computer Science, Data Science, Statistics, Engineering, Mathematics, Economics).
• Experience with time-series modeling and anomaly detection.
• Familiarity with deep learning and generative AI.

This role is ideal for a Data Scientist who wants to work at the cutting edge of AI and ML, leveraging LLMs, NLP, and predictive analytics to drive meaningful impact.

Mid-Senior level

Contract

Engineering, Information Technology, and Business Development

IT Services and IT Consulting, Technology, Information and Media, and Business Consulting and Services