Develop machine learning models, contribute to feature engineering, and model validation processes. Collaborate with senior team members in selecting and optimizing models for various data-driven projects. Apply machine learning algorithms to achieve objectives and communicate findings and risks. Experiment with different algorithms and techniques to enhance model performance. Contribute to the development of machine learning pipelines and participate in the implementation and validation of models. Demonstrate excellent coding and debugging skills.

Collaborate with the cross-functional teams on data-centric projects, assisting in data analysis and model implementation. Execute project tasks aligned with project timelines and objectives under the guidance of senior team members. Actively take part in data collection and preparation for various machine learning projects and tasks. Document the methodologies, findings, and outcomes of model experiments and present the results and findings to the team. Communicate technical findings effectively to team members and assist in presenting insights to stakeholders. Learn and adopt best practices in data analysis, model development, and validation to contribute to robust solutions. Mentorship and Collaboration: Engage in continuous learning, staying updated on emerging trends and techniques in data science. Collaborate with peers, actively participating in knowledge sharing sessions and contributing to a collaborative team environment. Seek guidance and mentorship from senior team members to enhance technical and analytical skills. Qualifications:  2+ years of experience as a data scientist involved in data extraction, analysis, and modeling. 2+ years of experience in Python and SQL or related tools for machine learning. Understanding of statistics and linear algebra. Through knowledge of machine learning algorithms and all stages of machine learning. Familiarity with neural networks and deep learning. Basic knowledge about AWS services and cloud databases. Proficiency in handling structured and unstructured data.   Our Commitment to Inclusivity and Diversity At G2, we are committed to creating an inclusive and diverse environment where people of every background can thrive and feel welcome. We consider applicants without regard to race, color, creed, religion, national origin, genetic information, gender identity or expression, sexual orientation, pregnancy, age, or marital, veteran, or physical or mental disability status.  Learn more about our commitments here Commitments