About Company:
LatentView Analytics is a leading global analytics and decision sciences provider, delivering solutions that help companies drive digital transformation and use data to gain a competitive advantage. With analytics solutions that provide a 360-degree view of the digital consumer, fuel machine learning capabilities, and support artificial intelligence.
We specialize in Predictive Modeling, Marketing Analytics, Big Data Analytics, Advanced Analytics, Web Analytics, Data Science, Data Engineering, Artificial Intelligence and Machine Learning Applications.
LatentView Analytics is a trusted partner to enterprises worldwide, including more than two dozen Fortune 500 companies in the retail, CPG, financial, technology and healthcare sectors.
Responsibilities
Design, construct, and refine machine learning (ML) and artificial intelligence (AI) models.
Apply MLOps practices to automate ML model deployment, monitoring, and maintenance.
Collaborate closely with cross-functional teams to integrate AI/ML models into larger systems and applications.
Preprocess, transform, and analyse extensive datasets for AI/ML model development.
Implement data security measures, including encryption, decryption, and PII data masking.
Leverage AWS services for facilitating AI/ML model development and deployment.
Sustain and optimise code deployment models.
Utilise programming languages like Python and tools such as Pandas and Pyspark for data engineering and manipulation tasks.
Apply software engineering rigour and best practices to machine learning, including CI/CD, automation, etc.
Ensure the integrity and reliability of data sources and outputs.
Effectively convey intricate ideas, findings, and concepts to both technical and non-technical stakeholders.
Facilitate the development and deployment of proof-of-concept machine learning systems

• 2-5 years experience in model development and deployment.
• Bachelors or Masters degree and/or equivalent professional experience
  Possess a minimum of 2+ years of experience in deploying and automating AI/ML models.
• Have a solid grasp of various machine learning algorithms, principles, and frameworks, including supervised, unsupervised, reinforcement learning models, and deep learning techniques.
• Minimum of 2 years of data engineering, data science, or data analysis-related work experience.
• Demonstrate strong programming skills, particularly in Python.
  Proficiently handle data preprocessing, exploration, and feature engineering.
  Possess experience with SQL, NoSQL databases, and data pipeline tools such as Apache Kafka or Apache Beam.
• Display a solid understanding of software development principles, DevOps methodologies, and cloud computing, with a focus on AWS.
• Familiarity with infrastructure as code (IAC) tools like Terraform or CloudFormation.
  Show awareness of data privacy, security, and governance practices.
• Exhibit excellent communication and collaboration abilities.
• Strong understanding of software testing, benchmarking, and continuous integration
• An AWS specialty certification in Machine Learning or Data Analytics is a plus.