SimpliSolve

Job Description

As a Data Scientist specializing in Time Series Forecasting, Language Modeling, and Classical Machine Learning at SimpliSolve, you will play a critical role in developing advanced analytical solutions that leverage temporal data, natural language processing techniques, and classical machine learning algorithms. You will collaborate with cross-functional teams to drive innovation and deliver impactful solutions to our clients.

Responsibility

• Lead efforts to develop and implement advanced time series forecasting models using state-of-the-art methodologies and tools.
• Apply your expertise in large language models to enhance our understanding of natural language dynamics and extract valuable insights from textual data.
• Utilize classical machine learning algorithms to process and analyze data from various domains and tasks.
• Conduct comprehensive exploratory data analysis to uncover patterns and insights within temporal, textual, and other data sets.
• Evaluate model performance and iteratively refine models to enhance accuracy and reliability in time series forecasting, language modeling, and classical machine learning tasks.
• Stay updated on the latest advancements in time series forecasting, natural language processing, classical machine learning, and related domains.
• Communicate findings and recommendations effectively to technical and non-technical stakeholders through reports, presentations, and visualizations.
• Mentor and provide guidance to junior team members, fostering their professional growth and development in time series forecasting, language modeling, and classical machine learning domains.

Requirements

• Master's or Ph.D. degree in Computer Science, Statistics, Mathematics, or a related field.
• 5+ years of hands-on experience working as a Data Scientist, with expertise in time series forecasting, large language models, and classical machine learning.
• Proficiency in programming languages such as Python or R, along with experience using relevant libraries (e.g., Pandas, NumPy, scikit-learn, TensorFlow, PyTorch).
• Strong understanding of statistical modeling, time series analysis, natural language processing, and classical machine learning techniques.
• Experience working with large-scale temporal, textual, and other data sets and implementing forecasting, language modeling, and classical machine learning solutions.
• Excellent analytical and problem-solving skills, with the ability to translate complex data into actionable insights.
• Effective communication and collaboration skills, with a track record of working effectively in cross-functional teams.
• Proven ability to thrive in a fast-paced, dynamic environment and deliver high-quality solutions within tight deadlines.