Data Scientist Intern
US CA Palo Alto
Machine Learning & Natural Language Processing (Data Science) Engineer Intern
Location – hybrid: Palo Alto, CA
The successful candidate will work with world-class data scientists and ML engineers on expanding the AI capabilities of Intapp products. If you have a passion for machine learning, experience with natural language processing and a demonstrated history of delivering results, then we are very interested in talking to you.
What you’ll do:
The main objective of the ML/NLP Internship at Intapp is to use different learning paradigms and architectures to build predictive models for different type of problems, including text categorization, natural language understanding and generation, data clustering and time series analysis, among others. The work will be applied to one (or more, if permitted by time) of the following problems of interest:
Prediction of type of work component (phase, task and activity) from time entries and narratives
Identification and discovery of categories (topic modeling) from unlabeled text data collections
Prediction of narrative templates (and full generation of narratives) from timecard history of matters
Document segmentation and categorization of terms in Outside Counsel Guidelines
Enrichment of current data representations by generating new features and rich metadata
Automatic collection and generation of ML/NLP resources for the Professional Services industry
Prediction of system failures from cloud component activity logs
The scope of the work includes defining a research question and work plan, setting up the experimental environment, preprocessing and preparing the data, training different variants of predictive algorithms, use evaluation metrics to assess the performance of the models, and prepare a final report.
What you’ll get:
Contribute to the research, design and construction of cutting-edge ML/NLP systems, applying emerging AI technologies to specific problems in the Professional Services industry.
Conduct project activities related to exploratory analysis and experimentation. Document, report and analyze results. Propose new ideas and related experimental work based on result analysis.
Work closely with our team of data scientists and ML engineers, attend technical meetings and contribute to the discussions.
The experience of being part of a growing public enterprise software company
What you’ll need:
Enrolled and working towards obtaining a BS, MS, or Ph.D in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Statistics or a related technical field.
Knowledge in machine learning and natural language processing, as well as computer science fundamentals (data structures, algorithms, big-O notation, concurrency, etc.)
Strong background in probability and statistics: statistical measures, distributions, hypothesis testing, regressions, etc.
Proficient in using Python (numpy, scipy, pandas, scikit-learn, spacy, pytorch, etc.) to implement machine learning models and algorithms.
Experience working with both relational SQL and NoSQL data stores.
Familiarity with the most commonly used Machine Learning algorithms and techniques (KNN, SVM, CRF, MLP, CNN, RNN, LSTM, etc.).
Familiarity with commonly used Natural Language Processing pipelines and techniques (POS tagging, Parsing, NER, NLU, TFIDF weighting, word embeddings, etc.)
Strong written and verbal communication skills; ability to explain technical concepts to a non-technical audience.
Bonus if you have:
Public Cloud AWS and/or Azure experience
Some low-level programming experience (C, C++, Java, Go, etc.)
Experience with big data & emerging technologies (Spark, Elasticsearch, Kafka, etc.)
What to Expect:
Our Summer 2025 Internship Program begins June 2, 2025, and is projected to end between August 8th and 22nd, 2025.
Your professional growth and development will be supported throughout the internship program via project work related to your academic and professional interests, mentorship, and engaging events with other interns and company leadership.
Our internship is hybrid, and interns will be expected in the office at least 3 days a week to get the full experience of the Intapp culture and networking opportunities.
Please visit Intapp Summer Internship to hear from our former interns about their internship experiences and check out Working at Intapp to learn more about what we value and why Intapp is a wonderful place to start your career!
Intapp provides equal employment opportunities to all qualified applicants and will make hiring decisions without regard to race, color, sex, sexual orientation, gender identity or expression, religion, national origin or ancestry, age, disability, marital status, pregnancy, protected veteran status, protected genetic information, political affiliation, or any other characteristic protected by federal, state or local laws. All offers are contingent upon passing a criminal history and other background checks if applicable to the position.
Please note: Intapp will not hire through text message, social media, or email alone. We will never extend a job offer unless you have been contacted directly by an Intapp recruiter and have participated in the interview process which will generally consist of 3 or more virtual or in person meetings. Please note that Intapp only uses company email addresses, which contain “@intapp.com” or “@dealcloud.com” to communicate with candidates via email. Intapp will never ask for financial information of any kind or for any payment during the job application process. We post all legitimate job openings on the Intapp Career Site at https://www.intapp.com/working-at-intapp/. If you believe you were a victim of such a scam, you may contact your local authorities. Intapp is not responsible for any claims, losses, damages, or expenses resulting from scammers.
Tags: Architecture AWS Azure Big Data Clustering Computer Science Elasticsearch Java Kafka LSTM Machine Learning ML models NLP NLU NoSQL NumPy Pandas Pipelines Python PyTorch Research RNN Scikit-learn SciPy spaCy Spark SQL Statistics Testing Topic modeling
Perks/benefits: Career development Startup environment Team events
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