Machine Learning Specialist

Whats the role?

If you are looking for an opportunity to solve deep technical problems, build innovative solutions, and work with top-notch developers, AGDATA has the role for you. You must be able to look at the big picture from both business and technology perspective, possess strong analytical, design, and problem-solving skills. You are not afraid of ambiguity, dealing with nebulous requirements, and get excited about difficult challenges.

In this role, you will have the opportunity to

Designs and develops scalable solutions and models. Performs research and testing to develop algorithms and predictive models.

Identifies trends, patterns, and anomalies found in big data sets by performing extensive data analysis to develop insights.

Performs data mining, cleaning, and aggregation processes to prepare data, implement data models, conduct analysis, and develop databases.

Develop processes to store model outputs in an SQL database and ensure seamless integration with reporting systems.

Interprets results from multiple structured and unstructured data sources using programming, statistical, and analytical techniques and tools.

Collaborates with teams to understand each data analysis projects' purpose, focus, and objectives.

Designs, develops, and implements valuable data-driven solutions for the organization. Integrates, tests, tunes, and monitors solutions. Proficient in big data tools, cloud platforms, multiple AI tools such as Python, Java, or R.

Mentors and train engineers on the AI/ML tools.

Builds processes for AI/ML projects

Participates in POCs & tool selection

Proficient with collaborating on code base in Git/ADO.

Typically requires a master's degree in computer science, mathematics, engineering or equivalent.

Technical Skills for a Data Scientist

8+ Years of experience in Data Science.

AI & Machine Learning Tools: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Scikit-Learn, TensorFlow, PyTorch, Keras, H2O.

Programming Languages: Python, R, Julia, SQL.

Data Tools: Pandas, dplyr, ggplot2, Tidyverse, data table.

Cloud & DevOps: AWS, Azure, Google Cloud, Docker, Kubernetes, Jenkins, Terraform, Pulumi, CloudFormation.

Databases: PostgreSQL, MySQL, MariaDB, NoSQL.

Other Skills: API Development, Data Cleaning & Transformation, Neural Networks, NLP, Computer Vision, Predictive Modeling, IoT, Blockchain, Quantum Computing.