NLP Engineer
Summary
Thoucentric is hiring an NLP Engineer in Bengaluru for a 6-month contract (extendable) on its India Analytics team. The role builds and scales ML/LLM models for text classification, sentiment analysis, topic modeling, and NER on unstructured data like social media and customer feedback, using Python NLP libraries, SQL, and dashboards in Tableau/Superset.
Job Description:
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. This role is a 6-month contract role with an option
to get extended and will sit under the Analytics Centre of Excellence in the
Global Ops Insights organization.
- 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.
Requirements
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
Benefits
Skills
- A/B Testing
- AI
- Analytics
- Data Science
- Data Visualization
- Deep Learning
- Feature Engineering
- Git
- Hive
- Hugging Face
- LLM
- Machine Learning
- Matplotlib
- NLP
- NoSQL
- NumPy
- pandas
- Plotly
- Power BI
- Python
- PyTorch
- SAS
- scikit-learn
- Seaborn
- spaCy
- Spark
- SQL
- Statistics
- Superset
- Tableau
- TensorFlow
- Teradata
- Transformers
- Version Control