Senior Data Scientist
Listed on 2026-01-29
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IT/Tech
Machine Learning/ ML Engineer, AI Engineer, Data Scientist, Data Analyst
Build the Future with Aspen View Technology Partners
At Aspen View, we are passionate about transforming the way organizations approach technology. We specialize in creating high-performing, nearshore IT teams to help North American clients innovate faster and more efficiently. As we continue to grow, we’re looking for exceptional people to join our team and help drive impactful change across industries.
Why Join Aspen View?At Aspen View, we’re more than a nearshore IT partner—we’re a people-first, purpose-driven company that believes great culture drives great outcomes. We’re passionate about connecting talent and technology to deliver measurable value for clients—and meaningful career paths for our people.
Here’s what you can expect:
- Competitive base
- Comprehensive benefits and wellness support
- Flexible work model: hybrid, remote, or in-office
- Real growth opportunities and leadership visibility
- Inclusive, respectful culture that blends U.S. innovation with Colombian heart
- A company that listens, invests in you, and celebrates wins together
As Senior Data Scientist, you’ll take on a high-impact role focused on building and scaling advanced models that balance customer acquisition with strong risk management. You’ll lead initiatives to allow more customers while carefully managing risks, working with advanced analytics and machine learning techniques to distinguish between high-risk and trustworthy profiles.
What you will do:- Design, build, and evaluate machine learning and deep learning models for classification, regression, recommendation, NLP, computer vision, and time-series forecasting.
- Apply deep learning techniques (e.g., CNNs, RNNs, LSTMs, Transformers) to solve complex, data-intensive problems.
- Lead the development of ML products, from model prototyping through production deployment, performance monitoring, and continuous improvement.
- Select appropriate architectures, optimize model performance, and use proper evaluation metrics based on the use case.
- Collaborate with product managers and engineers to translate business challenges into deployable solutions using AI/ML.
- Design automated pipelines for data preprocessing, feature engineering, training, and inference (batch or real-time).
- Evaluate model drift, monitor performance post-deployment, and implement retraining pipelines as part of a production MLOps system.
- Mentor junior data scientists, contribute to code reviews, and lead technical discussions across the data science and engineering teams.
- Bachelor’s degree in Computer Science, Statistics, Applied Math, or related field (Master’s or PhD strongly preferred).
- 7+ years of industry experience in applied machine learning, with 5+ years focused on deep learning and neural network applications.
- Proficiency in Python and ML libraries such as scikit-learn, XGBoost, Tensor Flow, Keras, or PyTorch.
- Deep understanding of neural networks, model regularization, overfitting/underfitting prevention, and GPU-accelerated training.
- Proven track record of building, evaluating, and deploying machine learning models at scale in production environments.
- Experience with cloud platforms (AWS/GCP/Azure), containerization, and model serving technologies.
- Excellent communication skills, with the ability to present complex findings to both technical and non-technical stakeholders.
- Hands-on experience with real-world applications of deep learning, such as recommendation engines, fraud detection, customer segmentation, document summarization, image recognition, or speech processing.
- Familiarity with MLOps tools (e.g., MLflow, Sage Maker, Airflow, Kubeflow).
- Experience with CI/CD for ML, feature stores, and real-time inference systems.
- Contributions to academic research, open-source ML projects, or ML/AI patents
Employer:
Aspen View is proud to be an equal opportunity employer. We believe in creating an environment where all employees feel welcome, valued, and empowered to succeed. We celebrate diversity and strive to build a culture of inclusion where all individuals, regardless of their race, color, gender, gender identity or expression, sexual orientation, disability, age, or any other characteristic, can thrive. We encourage applicants from all walks of life to join our team and make a lasting impact.
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