Compunnel, Inc.
Job Summary:
We are seeking a highly skilled and experienced Data Scientist to join our team. The ideal candidate will have 8–10 years of experience in data science with a focus on regression methods and unsupervised machine learning. This role requires strong technical expertise, the ability to handle large datasets, and a collaborative mindset to support data-driven decision-making. Key Responsibilities:
• Develop and implement regression models using XGBoost and neural networks • Apply unsupervised machine learning techniques such as PCA, k-means, and SVMs • Conduct data preprocessing, feature engineering, and model evaluation • Collaborate with cross-functional teams to translate business needs into technical solutions • Optimize and fine-tune machine learning models for performance and scalability • Stay current with advancements in machine learning and AI technologies • Communicate findings and insights to technical and non-technical stakeholders Required Qualifications:
• Minimum of 8–10 years of experience in data science or a related field • Strong understanding of machine learning algorithms and techniques • Hands-on experience with XGBoost, neural networks, PCA, k-means, and SVMs • Proven track record of deploying machine learning models in production environments • Experience working with large datasets and distributed computing frameworks • Ability to work independently and collaboratively within a team environment • Strong problem-solving skills and attention to detail • Effective communication skills for presenting technical concepts Preferred Qualifications:
• Experience with DataBricks • Familiarity with data visualization tools and techniques • Experience working in cross-functional team environments Technical Skills:
• Proficiency in Python and SQL (required) • Experience with DataBricks (preferred)
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We are seeking a highly skilled and experienced Data Scientist to join our team. The ideal candidate will have 8–10 years of experience in data science with a focus on regression methods and unsupervised machine learning. This role requires strong technical expertise, the ability to handle large datasets, and a collaborative mindset to support data-driven decision-making. Key Responsibilities:
• Develop and implement regression models using XGBoost and neural networks • Apply unsupervised machine learning techniques such as PCA, k-means, and SVMs • Conduct data preprocessing, feature engineering, and model evaluation • Collaborate with cross-functional teams to translate business needs into technical solutions • Optimize and fine-tune machine learning models for performance and scalability • Stay current with advancements in machine learning and AI technologies • Communicate findings and insights to technical and non-technical stakeholders Required Qualifications:
• Minimum of 8–10 years of experience in data science or a related field • Strong understanding of machine learning algorithms and techniques • Hands-on experience with XGBoost, neural networks, PCA, k-means, and SVMs • Proven track record of deploying machine learning models in production environments • Experience working with large datasets and distributed computing frameworks • Ability to work independently and collaboratively within a team environment • Strong problem-solving skills and attention to detail • Effective communication skills for presenting technical concepts Preferred Qualifications:
• Experience with DataBricks • Familiarity with data visualization tools and techniques • Experience working in cross-functional team environments Technical Skills:
• Proficiency in Python and SQL (required) • Experience with DataBricks (preferred)
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