Kantiv is a fast‑growing technology firm that focuses on building AI‑driven solutions for businesses across sectors such as finance, healthcare, and e‑commerce. Founded by a group of seasoned data engineers and scientists, the company has quickly established a reputation for delivering high‑impact analytics platforms that help clients turn raw data into actionable insights. With a collaborative culture that encourages experimentation and continuous learning, Kantiv invests heavily in research, open‑source contributions, and employee upskilling, making it an attractive destination for early‑career professionals looking to make a mark in data science. As a Data Scientist at Kantiv, you will be part of a dynamic team that designs, develops, and deploys machine‑learning models to solve real‑world business problems. You will work closely with product managers, data engineers, and domain experts to understand requirements, translate them into analytical solutions, and ensure that models are production‑ready and scalable. The role offers exposure to the entire data pipeline—from data ingestion and cleaning to model monitoring and performance tuning—providing a holistic view of the data science lifecycle. Key Responsibilities: 1. Collect, clean, and preprocess large structured and unstructured datasets from multiple sources. 2. Conduct exploratory data analysis to uncover patterns, trends, and anomalies. 3. Build, train, and validate predictive and classification models using statistical and machine‑learning techniques. 4. Deploy models into production environments using APIs or cloud services and monitor their performance. 5. Collaborate with cross‑functional teams to integrate model outputs into business workflows and dashboards. 6. Write clear documentation and present findings to both technical and non‑technical stakeholders. 7. Stay updated with the latest research in AI/ML and propose innovative solutions to improve existing products. 8. Participate in code reviews, contribute to shared codebases, and ensure adherence to best coding practices. 9. Assist in building data pipelines and feature stores to support model training and inference. 10. Mentor interns and junior analysts, fostering a culture of knowledge sharing. Tech Stack: Python, R, SQL, Pandas, NumPy, Scikit‑learn, TensorFlow/PyTorch, Docker, Kubernetes, AWS/GCP, Git, Tableau/PowerBI. Growth Path: Starting as an early‑career Data Scientist, you can progress to Senior Data Scientist, Lead Data Scientist, and eventually Head of Analytics or AI. Kantiv encourages internal mobility, offering opportunities to move into product management, data engineering, or research roles based on interests and performance. Why Join Kantiv? The company offers a fully remote work model, flexible hours, and a supportive environment that values curiosity and impact. Employees receive competitive compensation, regular learning stipends, and access to mentorship from industry veterans. If you are passionate about turning data into strategic advantage and want to grow in a cutting‑edge AI ecosystem, Kantiv provides the platform to accelerate your career.