Senior Analyst
1 month ago
Function: Data Science and Analysis - Data Analysis / Business Intelligence, Data Science / Machine Learning
About the Role :
We are seeking a sharp and passionate Sr. Analyst - Data Science to join our growing Data Science team. You will play a key role in leveraging the power of data to solve complex business problems and drive significant impact across the organization.
Responsibilities :
- Design and develop advanced machine learning models using algorithms like NLP, forecasting, prediction, and various analytical techniques.
- Participate in the entire data science lifecycle, from data acquisition, cleaning, and feature engineering to model training, evaluation, and deployment.
- Collaborate with business stakeholders to understand their needs, translate them into actionable insights, and communicate findings effectively.
- Build and maintain robust documentation for all models, capturing the objective, development process, chosen algorithms, validation methods, and implementation details.
- Continuously stay updated on the latest advancements in data science and machine learning methodologies.
- Participate in knowledge sharing and mentor junior team members.
Technical Skills :
- Programming Languages: Python (proficient), familiarity with R (a plus)
-Machine Learning Libraries: Scikit-learn, TensorFlow, PyTorch (experience with at least one)
- Statistical Analysis: Strong understanding of statistical methods, hypothesis testing, and Bayesian modeling
- Data Wrangling: Experience with data manipulation tools and techniques
- Data Visualization: Ability to create clear and compelling data visualizations
- Cloud Platforms (a plus): AWS, Azure, GCP
Requirements :
- Master's degree in Statistics, Computer Science, Data Science, or a related field (or) Bachelor's degree with significant work experience.
- Minimum 3-5 years of experience in data science or a related field.
- In-depth knowledge of machine learning algorithms for NLP, forecasting, prediction, and analytics.
- Strong understanding of traditional statistical analysis, Bayesian modeling, traditional machine learning, and deep learning concepts.
- Experience building and deploying machine learning models in production environments (a plus).
- Excellent communication and collaboration skills.
- Ability to manage multiple projects simultaneously and prioritize tasks effectively.
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