Data Scientist II

Who We Are

Robert Half, one of FORTUNE’s World’s Most Admired Companies and a Fortune 100 Best Companies to Work For is hiring for a Data Scientist II to join the Data Science department.

About the Role:

Ready to revolutionize the future of data-driven decision-making? Join our pioneering Data Science team as we embark on an exciting journey to unlock insights, drive innovation, and shape the landscape of our organization's success. If you're passionate about leveraging cutting-edge generative AI technologies and transforming raw data into actionable insight, we want you on our team!"

The Data Scientist II will be responsible for leading advanced data analytics projects, leveraging Azure and Microsoft data services and building Gen AI agents. This role demands a deep understanding of data science methodologies, machine learning algorithms, Gen AI concepts and big data technologies. The incumbent will work closely with cross-functional teams to understand business needs and formulate and execute data science solutions that drive significant business impact.

What You'll Do:

Data Analytics and Modeling:

• Develop and implement advanced predictive models and statistical analysis using a variety of machine learning algorithms.
• Suggest algorithms or models appropriate for specific use cases and applications.
• Analyze and extract relevant information from large amounts of historical business data to help automate and optimize key processes with business teams.
• Apply technical solutions to business problems and questions using large scale data analytics and machine learning; create highly calibrated solutions for business problems.
• Work closely with software engineering teams to drive real-time model experiments, implementations and new feature creations.
• Continuously evaluate and refine models based on performance metrics.
• Utilize cloud technologies such as Azure Machine Learning, Azure Databricks, and other Microsoft data services for data processing, model building, and deployment.

Large Language Model Fine-tuning:

• Enhance and evolve the performance of large language models by refining their capabilities through targeted fine-tuning.
• Steer both the research trajectory and the practical engineering efforts of the team.
• Formulate and enact algorithms for model enhancement, tweak critical hyperparameters, and heighten overall model efficiency.
• Guarantee the integrity and relevance of datasets by conducting thorough preprocessing and data analysis within the fine-tuning workflow.
• Conduct assessments on fine-tuned models, making necessary modifications to boost their effectiveness.
• Enhance performance of large language models by using prompt engineering, useful personas and retrieval-based techniques.
• Perform benchmarking on large language models with human in the loop and iteratively increase model performance.
• Design and build multi-agent workflows to solve complex business problems.
• Foster a cooperative environment within the team, providing guidance to peers to ensure a smooth fine-tuning operation that yields superior results.
• Stay at the forefront of advancements in large language model technologies and applications, perpetually refining technical expertise in model fine-tuning.

Data Management and Strategy:

• Collaborate with IT and data engineering teams in an enterprise setting to integrate data science solutions into the broader tech stack and data strategy.

Business Collaboration and Insights:

• Work closely with business stakeholders to identify opportunities for leveraging company data to drive business solutions.
• Translate complex data-driven findings into actionable business insights and communicate these effectively to non-technical stakeholders.

Research and Development:

• Stay abreast of industry trends and advancements in data science, large language models and Azure technologies.
• Conduct research to explore new methodologies and technologies that can enhance the organization's data analytics capabilities.

What You'll Need:

• Bachelor's degree in Statistics, Computer Science, Mathematics or equivalent required; Master's or PhD highly preferred.
• 5 years of professional experience in data science, with a record in designing and implementing large-scale data science projects.
• 5 years of industry experience in predictive modeling and large data analysis.
• Knowledge of open-source large language models and experience with evaluating and recommending appropriate models for specific use cases.
• 3+ years of experience in using big data platforms and technologies such as Hadoop, Azure data lake, Azure Cosmos DB, Pig, Hive, HBase, etc.
• 3+ years of hands-on experience in statistical modeling, data mining, large data analysis and predictive modeling; text mining a major plus.
• 3+ years of experience in regression, classification and clustering methods such as GLM, LR, SVM, LVQ, SOM, Neural Networks.
• Experience with two or more of the following: Python, PERL, Matlab or Scala.
• Expertise in various machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Excellent analytical, problem-solving, and communication skills.
• Excellent communication skills, with a proven ability to translate technical findings into business recommendations and strategies.
• Certifications in Azure data services or advanced analytics preferred.