Data Science

Principal Analyst – MLOps Engineer

Role Overview
We are seeking a highly skilled Senior MLOps Engineer with 8+ years of experience to join our team. The ideal candidate will have extensive expertise in model deployment, model monitoring, and productionizing machine learning models. You will play a crucial role in designing and implementing efficient workflows for AI programming and team communication, ensuring seamless integration of ML solutions within our organization.
Key Responsibilities:
• Workflow Design & Implementation: Oversee the implementation of workflows for AI programming and team communication, ensuring optimal collaboration and efficiency.
• Model Deployment: Manage and optimize model deployment processes, including the use of Kubernetes for containerized model deployment and orchestration.
• Model Registry Management: Maintain and manage a model registry to track versions and ensure smooth transitions from development to production.
• CI/CD Implementation: Develop and implement Continuous Integration/Continuous Deployment (CI/CD) pipelines for model training, testing, and deployment, ensuring high code quality through rigorous model code reviews.
• Model Monitoring & Optimization: Design and implement model inference pipelines and monitoring frameworks to support thousands of models across various pods, optimizing execution times and resource usage.
• Team Leadership & Training: Manage, mentor, and train junior engineers, fostering their growth and learning while overseeing a large team
• Collaboration with Data Science Teams: Train and collaborate with data science team members on best practices in tools such as Kubeflow, Jenkins, Docker, and Kubernetes to ensure smooth model productionization.
• Reusable Frameworks Development: Draft designs and apply reusable frameworks for drift detection, live inference, and API integration.
• Cost Optimization Initiatives: Propose and implement strategies to reduce operational costs, including optimizing models for resource efficiency, resulting in significant annual savings.
• Documentation & Standards Development: Produce MLE standards documents to assist data science teams in deploying their models effectively and consistently.
Qualifications:
• 8+ years of experience in MLOps, model deployment, and productionizing machine learning models.
• Proficient in Kubernetes, model monitoring, and CI/CD practices. Experience working in the Azure environment.
• Strong understanding of model registry concepts and best practices.
• Experience with programming languages and ML frameworks (e.g., TensorFlow, PyTorch).
• Proven track record of optimizing ML workflows and processes.
• Excellent communication and leadership skills, with experience in mentoring and training team members.
• Ability to work in a fast-paced, collaborative environment.

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Senior Principal Analyst – Data Science (Gen AI)

Key Responsibilities:

• Apply software and AI engineering patterns and principles to design, develop, test, integrate, maintain and
troubleshoot complex and varied Generative AI software solutions and incorporate security practices in newly
developed and maintained applications.
• Collaborate with cross-functional teams to define AI project requirements and objectives, ensuring alignment
with overall business goals.
• Conduct research to stay up to date with the latest advancements in generative AI, machine learning, and deep
learning techniques and identify opportunities to integrate them into our products and services, optimizing
existing generative AI models and RAG for improved performance, scalability, and efficiency, developing and
maintaining pipelines and RAG solutions including data preprocessing, prompt engineering, benchmarking and
fine-tuning.
• Develop clear and concise documentation, including technical specifications, user guides and presentations, to
communicate complex AI concepts to both technical and non-technical stakeholders.
• Independently handle complex issues with minimal supervision, while escalating only the most complex issues
to appropriate staff

Qualifications:
• Bachelor’s degree (B. Tech/B.E.) or master’s degree (M. Tech/M.E.) in Computer Science, Information
Technology, or a related field.
• Minimum of 8 years of related AI/ML work experience
• You are proficient in Python and have experience with machine learning libraries and frameworks. Proficient in
Python, TensorFlow, PyTorch, and other relevant AI/ML libraries and frameworks.

• NLP & LLM Expertise: Strong experience (4+) specifically with NLP applications and LLMs (such as GPT, BERT,
etc.), including model training, fine-tuning, and deploying at scale.
• Cloud: Hands-on experience with cloud services (AWS, GCP, or Azure) for AI/ML deployment.
• Have a deep understanding of industry leading Foundation Model capabilities and its application.
• 2+ years of experience with implementing information search and retrieval at scale (RAG applications),
using a range of solutions ranging from keyword search to semantic search using embeddings.
• You are familiar with cloud-based Generative AI platforms and services
• Full stack software engineering experience to build products using Foundation Models
• Confirmed experience architecting applications, databases, services or integrations

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Senior Principal Analyst-AI Engineering

Responsibilities

We are seeking a highly skilled and motivated Senior Principal Analyst to join our team. The ideal candidate will
possess a strong technical background with expertise in various programming languages and data technologies,
Data Science and Artificial Intelligence coupled with exceptional business acumen and communication skills. As a
Senior Principal Analyst, you will be responsible for leadingtechnical initiatives, designing innovative solutions, and
providing expert consultation to our clients.

Key Responsibilities:
• Develop and implement machine learning models (classification, regression) using advanced techniques.
• Select features, build, and optimize classifiers and regressors using traditional ML methods such as decision
trees, random forests, and gradient boosting.
• Perform data pre-processing, including data cleaning and transformation for analysis.
• Leverage statistical methods to analyze datasets, perform hypothesis testing, and implement predictive models.
• Lead end-to-end model development lifecycle: from data wrangling to deployment.
• Mentor junior data scientists and guide them in the application of machine learning algorithms.
• Collaborate with business stakeholders to translate their needs into actionable data-driven solutions.
Technical Skills:
• Advanced proficiency in Python and libraries such as scikit-learn and XGBoost.
• Strong understanding of ML algorithms (SVM, KNN, Naive Bayes) and statistical techniques (regression,
clustering, time-series analysis).
• Expertise in model validation and evaluation techniques (cross-validation, confusion matrix, AUC-ROC).
• Experience with data visualization tools (Tableau, Power BI) and SQL for data extraction.
• Familiarity with cloud environments (AWS, GCP).
Qualifications:
• Bachelor’s or master’s degree in computer science, statistics, or related fields.
• 8+ years of experience in building and deploying traditional machine learning models.

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Senior Principal Analyst (SPA) – Data Science

Responsibilities

We are seeking a highly skilled and motivated Senior Principal Analyst to join our team. The ideal candidate will
possess a strong technical background with expertise in various programming languages and data technologies, Data
Science and Artificial Intelligence coupled with exceptional business acumen and communication skills. As a Senior
Principal Analyst, you will be responsible for leading technical initiatives, designing innovative solutions, and providing expert consultation to our clients.

Key Responsibilities:

• Develop & implement machine learning models & algorithms to extract insights from large datasets.
• Select features, build, and optimize classifiers/regressors using machine learning and deep learning techniques.
• Process, cleanse, and verify the integrity of data used for analysis.
• Perform data mining and analytics to support continuous risk monitoring and risk assessments.
• Utilize various statistical techniques and predictive modeling to drive and identify indicators of risk.
• Design & maintain effective information and data models that align with the organization’s data requirements and
objectives.
• Translate complex business problems into technical solutions and architectures.
• Develop and present Proof of Concepts (POCs) and technical client presentations.
• Mentor and provide guidance to junior data scientists and analysts.

Technical Skills:

• Advanced proficiency in Python coding for AI/ML algorithms and data analytics.
• Strong grasp of machine learning algorithms: Random Forest, Gradient Boosting, Naive Bayes, SVM, KNN.
• Deep understanding of deep learning techniques: DNN, CNN, RNN, LSTM, Autoencoders.
• Proficiency with ML/AI software and tools: scikit-learn, TensorFlow, PyTorch, CARET.
• Solid understanding of statistical concepts: Sampling Theory, Descriptive Statistics, Probability Distributions,
Statistical Tests, Dimensionality Reduction, Hypothesis Testing, Maximum Likelihood Estimators, and Inference.
• Expertise in model validation, hyperparameter tuning, and model selection techniques: Cross-validation, Bootstrap methods.
• Proficiency in data analytics tools for queries and analyses, and data visualization platforms for summaries,
predictive analyses, comparative analyses, dashboards, and reports.
• Strong command of query languages: SQL and Spark.
• Familiarity with cloud platforms such as AWS and GCP is a plus.

Qualifications:

• Bachelor’s or master’s degree in computer science, Information Technology, Engineering, or a related field.
• Minimum of 10 years of experience in a similar role with recent 8 years of relevant experience.
• Relevant certifications in programming languages, data technologies, or cloud platforms would be advantageous.

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Senior Principal Analyst- Data Science

Responsibilities

We are seeking a highly skilled and motivated Senior Principal Analyst to join our team. The ideal candidate will
possess a strong technical background with expertise in various programming languages and data technologies, Data
Science and Artificial Intelligence coupled with exceptional business acumen and communication skills. As a Senior
Principal Analyst, you will be responsible for leading technical initiatives, designing innovative solutions, and providing expert consultation to our clients.

Key Responsibilities:

• Develop & implement machine learning models & algorithms to extract insights from large datasets.
• Select features, build, and optimize classifiers/regressors using machine learning and deep learning techniques.
• Process, cleanse, and verify the integrity of data used for analysis.
• Perform data mining and analytics to support continuous risk monitoring and risk assessments.
• Utilize various statistical techniques and predictive modeling to drive and identify indicators of risk.
• Design & maintain effective information and data models that align with the organization’s data requirements and
objectives.
• Translate complex business problems into technical solutions and architectures.
• Develop and present Proof of Concepts (POCs) and technical client presentations.
• Mentor and provide guidance to junior data scientists and analysts.

Technical Skills:

• Advanced proficiency in Python coding for AI/ML algorithms and data analytics.
• Strong grasp of machine learning algorithms: Random Forest, Gradient Boosting, Naive Bayes, SVM, KNN.
• Deep understanding of deep learning techniques: DNN, CNN, RNN, LSTM, Autoencoders.
• Proficiency with ML/AI software and tools: scikit-learn, TensorFlow, PyTorch, CARET.
• Solid understanding of statistical concepts: Sampling Theory, Descriptive Statistics, Probability Distributions,
Statistical Tests, Dimensionality Reduction, Hypothesis Testing, Maximum Likelihood Estimators, and Inference.
• Expertise in model validation, hyperparameter tuning, and model selection techniques: Cross-validation, Bootstrap methods.
• Proficiency in data analytics tools for queries and analyses, and data visualization platforms for summaries,
predictive analyses, comparative analyses, dashboards, and reports.
• Strong command of query languages: SQL and Spark.
• Familiarity with cloud platforms such as AWS and GCP is a plus.

Qualifications:

• Bachelor’s or master’s degree in computer science, Information Technology, Engineering, or a related field.
• Minimum of 10 years of experience in a similar role with recent 8 years of relevant experience.
• Relevant certifications in programming languages, data technologies, or cloud platforms would be advantageous.

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