Research Data Analyst
2 days ago
We are seeking a highly skilled Data Research Specialist who can leverage advanced AI, data science, and automation to identify, enrich, and deliver high-quality B2B leads. This role is integral to enhancing our sales pipeline by providing actionable intelligence, predictive insights, and accurate datasets for our business development and marketing teams.
Lead Identification & Enrichment: Research and build high-quality B2B lead databases using AI/ML-based tools, web scraping frameworks, and third-party APIs. Enrich and validate prospect data (e.g., firmographics, technographics, buying signals) from multiple data sources like LinkedIn, Crunchbase, ZoomInfo, and industry directories.
- Data Analysis & Predictive Modeling: Apply machine learning techniques to score and prioritize leads based on historical performance. Conduct trend analysis to refine Ideal Customer Profiles (ICP) and suggest new target segments.
- Build and maintain Python scripts or automated pipelines for large-scale data scraping and cleaning. Evaluate and integrate LLM-based tools (e.g., LangChain, OpenAI APIs) for intelligent data extraction and enrichment.
- Partner with Sales and Marketing teams to align data research efforts with campaign goals. Deliver dashboards and insight reports (Power BI, Tableau, or similar) to track lead quality, conversion trends, and market opportunities. Support A/B testing of targeting strategies and provide data-driven recommendations.
- Compliance & Data Integrity: Ensure adherence to data privacy regulations (GDPR, Indian DPDP Act) and ethical AI usage. Maintain data hygiene and prevent duplication across CRM systems like Salesforce or HubSpot.
Bachelor’s/Master’s degree in Data Science, Computer Science, Statistics, or a related field.
- 3–5 years of experience in B2B lead research, sales intelligence, or data analytics roles.
- Proven expertise in Python/R for data scraping, cleaning, and analysis.
- Experience with web scraping tools like BeautifulSoup, Scrapy, or Selenium.
- Proficiency with data visualization platforms (Power BI, Tableau) and CRM systems (HubSpot, Salesforce).
- Knowledge of machine learning frameworks (Scikit-learn, TensorFlow, or PyTorch) for predictive modeling.
- Familiarity with Gen-AI/LLM tools (e.g., ChatGPT API, Hugging Face models) for data enrichment and summarization.
Experience with vector databases or embedding-based search for advanced prospect matching.
- Understanding of big data frameworks (Spark, Hadoop) for large-scale processing.
- Knowledge of industry-specific B2B sales cycles (SaaS, gaming, IT services).
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