This role involves collaborating with diverse teams to integrate data strategies, ensuring compliance with relevant regulations and policies, and staying informed of industry advancements to recommend best practices. The specialist is expected to have extensive experience in data governance, strong analytical and communication skills, and proficiency in technical skills like SQL and Python.
Principal Analyst (Machine Learning Engineer) Read More »
Job Title: Senior Data Engineer
Type: Fulltime
Experience: 7 -12 yrs
Location: Remote
Skills: SQL , Python, ML Understanding and Open Source Frameworks
Job Description:
Create and optimize complex SQL queries for data extraction, manipulation, and reporting.
Develop robust Python scripts and applications for data processing, automation.
Collaborate with cross-functional teams to define architecture and implement best practices in cloud-native development.
Monitor and troubleshoot performance issues, ensuring reliability and scalability of cloud solutions.
Write clean, maintainable, and well-documented code following software development best practices.
Ensure data security and compliance with organizational and industry standards.
Strong hands-on expertise with SQL, including writing complex queries and optimizing database performance.
Advanced Python programming skills, including experience with libraries and frameworks relevant to data processing and integration.
Senior Data Engineer Read More »
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.
Principal Analyst – MLOps Engineer Read More »
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
Senior Principal Analyst – Data Science (Gen AI) Read More »
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.
Senior Principal Analyst-AI Engineering Read More »
Factspan Overview: Factspan is a pure play data and analytics services organization. We partner with fortune 500 enterprises to build an analytics center of excellence, generating insights and solutions from raw data to solve business challenges, make strategic recommendations and implement new processes that help them succeed. With offices in Seattle, Washington and Bengaluru, India; we use a global delivery model to service our customers. Our customers include industry leaders from Retail, Financial Services, Hospitality, and technology sectors.
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, 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:
Technical:
• Proficiency in programming languages including Python, SQL, Spark, and PySpark.
• Extensive experience in Data Warehousing, Solution Architecture, ETL processes, and SQL skills.
• In-depth knowledge of data integration frameworks and techniques.
• Hands-on experience with Cloud platforms such as AWS, GCP, Azure, and/or Snowflake.
• GCP knowledge including experience in Big Query, Dataflow, Cloud Composer, Dataproc and GCS
• 5+ years of experience in solutioning and design in data & analytics projects
• Experience in handling multiple projects as a Data Architect and/or Solution Architect
• 5+ years of hands-on experience in implementing data Integration frameworks to ingest terabytes of data in batch and real-time to an analytical environment x
• 3+ years of experience in Cloud data migration (GCP preferred)
• Hands-on experience with ETL pipeline development and functional programming
Business:
• Ability to translate complex business problems into technical solution architectures.
• Develop and demonstrate Proof of Concepts (POCs) related to data ingestion and data quality. • Design and implement frameworks and reusable codes to streamline processes.
• Conduct technical client presentations and provide consulting services to clients.
Behavioural:
• Demonstrated passion for the role and commitment to the company’s objectives.
• Strong technical aptitude and ability to stay updated with the latest technological trends.
• Excellent written and verbal communication skills.
• Analytical and creative thinking abilities to solve complex problems.
• Collaborative mindset with the ability to work effectively in a team environment.
• Self-driven and proactive approach towards achieving goals.
Qualifications:
• Bachelor’s or master’s degree in computer science, Information Technology, or related field.
• Minimum of 10 years of experience in a similar role with recent 8 years of relevant experience
• Proven track record of successfully delivering technical solutions to clients.
• Relevant certifications in programming languages, data technologies, or cloud platforms would be advantageous
GCP Data Engineer Read More »
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.
Senior Principal Analyst (SPA) – Data Science Read More »
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.
Senior Principal Analyst- Data Science Read More »