NLP Engineer

Location

Experience:

Domain

We are looking for an advanced analyst in our India Analytics team who works closely with the Community Voice team. The analyst must have functional expertise in building analytical solutions using unstructured text data and be a trusted partner to business teams and leaders, to provide scalable insights and solutions enabling data driven decisions.

• Build, maintain, and scale ML/LLM models for text classification, sentiment analysis, entity recognition, and other NLP tasks using Python libraries such as NLTK, SpaCy, Hugging Face Transformers, and Gensim.
• Utilize SQL and other database tools to query, analyze, and manipulate data stored in multiple relational databases.
• Work on unstructured and semi-structured data sources like social media feeds, reviews, surveys, and customer feedback to generate business insights.
• Implement advanced analytics techniques for clustering, topic modeling (LDA, LSA), and semantic analysis of textual data.
• Develop and maintain dashboards and data visualizations using tools like Tableau, Superset, or Python visualization libraries (Matplotlib, Seaborn, Plotly).
• Collaborate closely with cross-functional teams, including data engineers, product managers, and business stakeholders, to translate business requirements into analytical solutions.
• Stay up to date with the latest trends and best practices in NLP, AI/LLMs and experiment with newer techniques to shift bias towards efficiency.
• Work on improving existing NLP models, pipelines, and workflows, ensuring performance optimization and scalability using feature engineering techniques.

Skills & Expertise:

• 5-8 years of industry experience and an Advanced degree in Business Analytics or other (Masters or PhD is a plus) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research)
• Proven track record of delivering full stack AI/ML projects from inception to business impact.
• Advanced level proficiency in Python, including libraries such as NLTK, spaCy, scikit-learn, numpy and pandas.
• Strong understanding of SQL/NoSQL, programming languages such as Python, R, SAS and Intermediate level knowledge of data foundations and databases like Presto, Hive, Teradata, Spark.
• Familiarity with linear regression, logistic regression, SVM, random forest, advanced concepts of NLP, KNN, K-Means, A/B testing, and multivariate testing,.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and statistical analysis.
• Hands-on experience in text classification, sentiment analysis, topic modeling, and named entity recognition (NER), proficiency in building and deploying machine learning models and analyzing unstructured data such as textual data, including social media, customer feedback, and reviews.
• Experience with data visualization tools such as Tableau, Power BI, or Matplotlib/Seaborn.
• Familiarity with Git or other version control systems, deep learning models for NLP tasks, such as transformers (e.g., BERT, GPT).
• Have a positive and solution-oriented mindset with an ability to maintain confidentiality and objectivity.
• Exceptional problem-solving abilities, self-motivation and ability to work autonomously, strong organizational and time management skills, with the ability to manage multiple priorities and meet deadlines.
• Excellent communication and collaboration skills with the ability to work effectively with internal teams in a cross-cultural and cross-functional environment.
• Ability to conduct exploratory data analysis (EDA) to uncover insights and trends in data and communicate findings to both technical and non-technical audiences