Data Scientist - Diss

Overview

We are looking for a Machine Learning Engineer to develop and deploy machine learning models, build NLP solutions, and optimize data pipelines. The ideal candidate will work on anomaly detection, time-series analysis, and automation while collaborating with cross-functional teams.

Key Responsibilities

• Machine Learning & NLP: Develop and deploy ML models for tasks like name screening, sentiment analysis, and text classification.
• Anomaly Detection & Time Series Analysis: Build predictive models using LSTM, SVD, and other techniques.
• API Development: Create APIs to integrate ML models into applications.
• Data Engineering: Design scalable ETL pipelines, clean and validate data, and manage time-series databases.
• Web Scraping & Automation: Develop automated data extraction solutions integrated with NLP.
• Data Visualization: Create reports and insights to support decision-making.
• Collaboration & Leadership: Work with business teams, mentor junior members, and contribute to team development.
  
  

Skills & Qualifications

• Strong knowledge of Python, TensorFlow, PyTorch, and Scikit-learn
• Experience with NLP tools (spaCy, NLTK, Hugging Face)
• Hands-on expertise in anomaly detection and predictive analytics
• Proficiency in SQL, Apache Spark, and cloud platforms (AWS/GCP/Azure)
• Experience with API development (Flask, FastAPI)
• Strong problem-solving and communication skills