Senior Data Scientist

Fractal Analytics•New York, NY

About The Position

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a ecosystem where human imagination is at the heart of every decision. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner. Role Overview Data Scientist with GenAI Experience Job Summary: We are seeking an experienced Data Scientist with a focus on Gen AI and a minimum of 5 years of industry experience. The ideal candidate will have a strong background in machine learning, statistical analysis, and data modeling, with a specific emphasis on extracting insights from textual data. This role involves working on complex NLP projects to derive meaningful patterns and knowledge from large datasets.

Requirements

Master's in Computer Science, Data Science, Statistics, or a related field.
Minimum of 5 years of professional experience in data science, with a focus on GenAi.
Strong programming skills in languages such as Python or R.
Expertise in using NLP libraries and frameworks such as NLTK, SpaCy, or TensorFlow.
Proficiency in machine learning techniques, including supervised and unsupervised learning.
Experience with deep learning frameworks like TensorFlow or PyTorch.
Strong understanding of text mining, information retrieval, and semantic analysis.
Excellent problem-solving and analytical skills.
Effective communication and collaboration skills.

Nice To Haves

Experience with cloud platforms (e.g., AWS, Azure) and big data technologies is a plus.

Responsibilities

Develop and implement NLP models for various applications, including text classification, sentiment analysis, entity recognition, and language translation.
Utilize machine learning and deep learning techniques to extract valuable information from unstructured text.
Preprocess and clean large volumes of text data to prepare it for analysis.
Implement techniques such as tokenization, stemming, and lemmatization.
Identify and engineer relevant features from text data to improve model performance.
Implement techniques to capture semantic relationships within the data.
Train, fine-tune, and validate NLP models using appropriate algorithms.
Evaluate model performance using metrics such as precision, recall, F1 score, and accuracy.
Conduct exploratory data analysis on textual datasets to uncover patterns, trends, and anomalies.
Use statistical methods to gain insights into the underlying structure of the data.
Work closely with data engineers, software developers, and domain experts to integrate NLP solutions into broader systems and applications.
Collaborate in defining project goals, requirements, and deliverables.
Optimize and fine-tune NLP algorithms for improved efficiency and accuracy.
Implement parallel processing and distributed computing techniques for large-scale data analysis.
Stay informed about the latest advancements and trends in NLP and machine learning.
Apply cutting-edge techniques to solve complex business problems.
Document methodologies, algorithms, and code for reproducibility and knowledge transfer.
Prepare clear and concise project reports and documentation.