Priyaranjan Dhar

• Currently responsible for building scalable Talent Intelligence/ Talent Analytics solutions by analyzing billion records of Public profile and job posting data with our team at Talent Intuition

Key Projects :

• NLP Entity extraction model- Custom NER models to auto extract and label key entities (like - hard skills, soft skills, qualifications, experience, job title, salary, etc.) from unstructured and messy profile and demand data.
• Introduced Workforce clustering and labeling Industry based on workforce distribution of across many function (Sales, Marketing, Software engineering, Technology, data and AI, Other engineering)
• Building skill Taxonomy: Working on Building skill taxonomy based on job demand data, Clustering closely associated /related skills
• Mine Associated and Related skills based on specific skill search
• Data Pipeline: Introduced ETL pipelines for processing raw profile data and produced ready to plugin data for custom client projects
• Working on Topic Modeling to cluster Similar Profiles and Job Postings
• Train and Develop junior data scientist

• Prime responsibility was to building Talent Intelligence Data Science team from scratch and introduce Talent Intelligence Data Science Solutions for Global Philips Talent Strategy
• Building ETL processes for Web scraping job posting data across competitors career page
• Introduced custom NER models for parsing key competitors insights and pulling competitive intelligence from job data and collaborate with Philips global Market intelligence team on competitors new product development, Innovation, New Office etc.
• Developed naive bayes classification model for Mining Key sentences/ Insights from text relevant to Market Intelligence
• Developed employee sentiment Analysis using Glassdoor Employee reviews helping Philips Talent Strategy to Identify Gaps in Employee engagement, benchmark with Key competitors, employee benefits analysis, etc
• Interview, hire, manage and train Philips Talent Intelligence Data Science Team
• Developed statistical models for estimating available talent pool supply for a given cost across US locations to help Global TA team in their decisionmaking and strategy
• Building PoC use cases and presentation to the leadership team for budget approvals on Technology and resource requirements
• Present findings and Insights to non technical users and stakeholders

• As Process Lead - Data Analytics and Marketing Intelligence my rsponsibilities were to support The APAC and Global category sourcing managers in their Sourcing and Hedging decisions and lead the CoE Machine Learning initiative for Cargill Strategic Sourcing and Procurement
• Crude Oil Price Prediction Model: Developed Models ridge regression models to Predict WTI Crude Oil Prices with more than 85% accuracy which helped the Category Managers in their hedging decisions and Mitigating risk for Sourcing and Procurement of Many Chemical and Packaging commodities like PE, PPE, PPT (Crude by products)
• Automation : Used OCR for converting Image files to computer readable text and applied NER models to auto extract key attributes from Supplier contract agreement such as start-date, end date, commodities, etc.
• Improving Spend taxonomy using supervised Machine learning techniques to label free text/ product description to L3 Spend categories

• Delivered end to end Custom client projects for fortune 500 Companies on Talent Analytics on Workforce Strategy, Competitive Talent Intelligence, Diversity Analysis, Location analysis, skill analysis etc.
• Helped data Engineering team to develop rule based algorithms to identify and filter skill from english text words
• Proven expertise on Handling and Managing large datasets
• Extablished data exploration projects and processes for pulling meaningful insights and statistical inferences from large talent and employment statistics datasets
• Delivered client ready dynamic Power-Bi , Excel dashboards and power point research reports
• Defined Processes for mining and deliver meaningful statistical inferences from workforce data on Salary cost, Talent pool, Employment, Hiring difficulty etc.

• Deliver Clients Projects and Analysis of employment statistics and employment data
• Delivering End to custom Talent research reports which includes pulling meaningful insights and draw statistical inferences from large pool of publicly available employment statistics and economic data from BLS, OECD, World Bank Data, IMF, U.S. Bureau of Economic Analysis, FRED etc.