Senior Machine Learning Engineer

Prescott Data

Innovating Data Solutions with Prescott Data | AI and Cloud Storage/Migration


As the Senior Machine Learning Engineer at Prescott Data, your primary responsibilities will include:

1.⁠ ⁠Model Development and Implementation:

Design, develop, and implement machine learning models for various applications.

Optimize and fine-tune existing models to improve performance.

2.⁠ ⁠Data Analysis:

Conduct thorough data analysis to understand patterns, trends, and insights.

Collaborate with data scientists and domain experts to preprocess and prepare data for modelling.

3.⁠ ⁠Algorithm Design:

Create and refine algorithms that drive predictive and prescriptive analytics.

Explore innovative approaches to solving complex problems using machine learning techniques.

4. Collaboration:

Work closely with cross-functional teams (including data engineers, software developers, and product managers) to integrate machine learning solutions into our products.

Communicate effectively to bridge the gap between technical and non-technical stakeholders.

5.⁠ ⁠Continuous Learning:

Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields.

Participate in conferences, workshops, and online courses to enhance your expertise.

6.⁠ ⁠Ethical AI Practices:

Ensure fairness, transparency, and accountability in all machine learning processes.

Address bias and ethical considerations when designing and deploying models.


The Senior Machine Learning Engineer role has the following requirements:

1.⁠ ⁠At least 2 years of Python scripting experience.

2.⁠ ⁠Minimum of 1 year working with machine learning algorithms.

3.⁠ ⁠Bachelor’s degree in Statistics, Computer Science, Software Engineering, or a related field in Mathematics.

4.⁠ ⁠Experience with cloud engineering.

Additional skills (not mandatory but advantageous):

1.⁠ ⁠Data science, analytics, and engineering experience.

2.⁠ ⁠Scripting with R.

3.⁠ ⁠MLops knowledge.


1.⁠ ⁠Strong programming skills.

2.⁠ ⁠Knowledge of data science principles.

3.⁠ ⁠Expertise in statistics.

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