We're looking for a seasoned Data Scientist with 3+ years of experience in AI/ML, preferably with some experience in Generative AI. You're a humble and collaborative individual who thrives in a fast-paced environment. You're passionate about developing and delivering data analytics and machine learning models that drive business impact. Master's degree (M.S.) in Data Science, Computer Science, Business Analytics, Machine Learning, Statistics, or a related quantitative field. 3+ years of experience in AI/ML, with proven experience developing and deploying machine learning models in a production environment. Strong proficiency in Python for data science and machine learning. Expertise in SQL for data querying, manipulation, and database interaction. Strong skills in data acquisition, algorithm design, and model development and refinement. Experience with big data technologies, cloud-based data platforms (e.g., GCP, AWS), and business intelligence tools (e.g., Power BI, Streamlit, Plotly Dash). Solid understanding of machine learning algorithms, statistical modeling, and data analysis techniques. Excellent oral, written, and interpersonal communication skills. Ph.D. in Data Science, Computer Science, Business Analytics, Machine Learning, Statistics, or a related quantitative field. 5+ years of experience in data science and analysis, including leadership or mentoring roles. Significant experience in Generative AI, including a strong understanding of ML frameworks, algorithms, and practical implementation. Experience in specialized areas such as Natural Language Processing (NLP), deep learning (e.g., TensorFlow, PyTorch), or recommendation systems. Experience with building and managing data pipelines, including familiarity with orchestration tools (e.g., Apache Airflow, Kubeflow) or DBT. Experience in sustainability and regulatory compliance domain is a plus. Certifications in Google Cloud Platform (GCP) or other cloud platforms. Experience with agile development methodologies and version control systems (e.g., Git). A record of publications or presentations in recognized journals or conferences. Acquire a deep understanding of business problems and translate them into appropriate technical solutions. Design, develop, and implement end-to-end AI/ML pipelines, from data ingestion and preprocessing to model training, evaluation, and deployment. Act as a full-stack data scientist to develop and deliver advanced analytics models, including classification, time series, LLM, and more. Write clean, efficient, and well-documented code in Python for data manipulation, feature engineering, and model development. Utilize SQL extensively for data extraction, transformation, and loading (ETL) from various relational databases. Collaborate internally and with data engineers to identify new and novel data sources, ensure robust data infrastructure, and explore their potential use in developing actionable business results. Monitor and maintain deployed AI/ML models, ensuring their ongoing performance, accuracy, and reliability. Analyze and interpret complex datasets to identify trends, patterns, and insights that inform model development and business decisions. Communicate technical concepts and analytical results effectively to both technical and non-technical stakeholders. Work independently with minimal guidance, taking ownership of projects and delivering results. Foster a collaborative team environment, showing the highest respect for team members and their contributions. Stay updated with the latest advancements in AI, machine learning, and data science technologies. Established and active employee resource groups
