Blend360 is hiring a
AI Data Scientist

Summary

The job is for a Lead Data Scientist at Blend360, a global marketing, analytics, and technology company. The role involves leading a team to provide AI solutions using advanced data science techniques and tools, working with clients to understand business problems, and deploying models within their architecture.

Requirements

• Consulting Experience
• Proven ability to lead a team
• Profound knowledge of deep learning principles and architectures, including CNNs, RNNs, and transformers, with the ability to apply these techniques to natural language processing tasks
• Deployment experience - Understanding of how to integrate models into production
• Engineering experience
• In-depth understanding of the workings of LLMs and the ability to manipulate model parameters to achieve desired outcomes in text generation
• Expertise in crafting effective prompts that guide AI models to generate desired outputs. Understand how different prompt structures influence AI behavior
• Experience with RAG models, which combine a retrieval component with a generator to enhance the quality and relevance of the AI's output. Understand how to effectively integrate external knowledge sources into AI responses
• Capability to train and fine-tune models on specific datasets to improve performance and ensure the relevance of the outputs to the task at hand
• MS degree in Statistics, Math, Data Analytics, or a related quantitative field
• At least 5 years of post graduate professional experience in Advanced Data Science, such as predictive modeling, statistical analysis, machine learning, text mining, geospatial analytics, time series forecasting, optimization
• Demonstrated Experience with NLP and other components of AI
• Experience implementing AI solutions
• Experience with one or more Advanced Data Science software languages (Python, R, SAS)
• Proven ability to deploy machine learning models from the research environment (Jupyter Notebooks) to production via procedural or pipeline approaches
• Experience with SQL and relational databases, query authoring and tuning as well as working familiarity with a variety of databases including Hadoop/Hive
• Experience with spark and data-frames in PySpark or Scala
• Strong problem-solving skills; ability to pivot complex data to answer business questions. Proven ability to visualize data for influencing
• Comfortable with cloud-based platforms (AWS, Azure, Google)

Responsibilities

• Lead a Team of Data Scientists providing AI Data Science Solutions to our clients
• Work with practice leaders and clients to understand business problems, industry context, data sources, potential risks, and constraints
• Work with practice leaders to get stakeholder feedback, get alignment on approaches, deliverables, and roadmaps
• Create and maintain efficient data pipelines, often within clients’ architecture
• Assemble large, complex data sets from client and external sources that meet functional business requirements
• Build analytics tools to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
• Perform data cleaning/hygiene, data QC, and integrate data from both client internal and external data sources on Advanced Data Science Platform
• Utilize deep learning principles and architectures, including CNNs, RNNs, and transformers, apply these techniques to natural language processing tasks
• Manipulate model parameters to achieve desired outcomes in text generation
• Craft effective prompts that guide AI models to generate desired outputs. Understand how different prompt structures influence AI behavior
• Use RAG models, and combine a retrieval component with a generator to enhance the quality and relevance of the AI's output. Understand how to effectively integrate external knowledge sources into AI responses
• Train and fine-tune models on specific datasets to improve performance and ensure the relevance of the outputs to the task at hand
• Conduct statistical data analysis, including exploratory data analysis, data mining, and document key insights and findings toward decision making
• Document predictive models/machine learning results that can be incorporated into client-deliverable documentation
• Assist client to deploy models and algorithms within their own architecture

Preferred Qualifications

Experience with Google Analytics, Adobe Analytics, Optimizely a plus