What are the responsibilities and job description for the Data Scientist position at Motion Recruitment?
We are partnering with a leading financial services client in Phoenix to hire a Data Science / Machine Learning Engineer to support the development and deployment of advanced analytics and AI-driven solutions. This role is ideal for someone who thrives in a fast-paced environment and has hands-on experience building, optimizing, and deploying machine learning models at scale.
Location: Phoenix, AZ (Hybrid – 3 days onsite per week)
Duration: Contract – Potential for Extension/Conversion
Key Responsibilities
- Design, develop, and deploy machine learning models for real-world financial use cases
- Work across the full ML lifecycle: data ingestion, feature engineering, model training, evaluation, deployment, and monitoring
- Build and implement both classical machine learning models (e.g., regression, classification, clustering) and NLP solutions (e.g., text classification, entity recognition, sentiment analysis)
- Collaborate with data engineers and business stakeholders to translate business requirements into scalable ML solutions
- Optimize model performance and ensure reliability in production environments
- Develop APIs and integrate ML models into existing enterprise systems
- Maintain proper documentation and ensure model governance, compliance,
Required Qualifications
- 5 years of experience in Data Science, Machine Learning Engineering, or a related field
- Proven hands-on experience building and deploying ML models in production environments
- Strong experience with Python and ML libraries such as scikit-learn, TensorFlow, PyTorch
- Experience with Natural Language Processing (NLP) techniques and frameworks (e.g., NLTK, spaCy, transformers)
- Experience with data manipulation and analysis using Pandas, NumPy
- Familiarity with cloud platforms such as AWS, Azure, or GCP
- Experience developing APIs (e.g., Flask, FastAPI) for model deployment
- Strong understanding of model evaluation, tuning, and performance optimization