Machine Learning

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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Principal Analyst – Data Science (LLM)

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 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 Principal Analyst, you will be responsible for leading technical initiatives, designing innovative solutions, and providing expert consultation to our clients.

Key Responsibilities:

Develop and fine-tune applications using Gemini LLM and other state-of-the-art NLP models.
Integrate Gemini LLM capabilities into existing platforms and create new, AI-driven solutions.
Design and implement efficient pipelines for training, evaluating, and deploying LLM-based applications.
Work with cross-functional teams to identify business use cases and translate them into technical solutions powered by LLMs.
Optimize model performance, latency, and scalability for production-grade deployments.
Conduct research on emerging trends in NLP and LLM technologies to drive innovation within the team.
Develop APIs and services to expose LLM capabilities to internal and external users.
Monitor deployed models, analyze their performance, and iteratively improve them based on user feedback and operational data.
Ensure adherence to ethical AI guidelines and implement robust measures for model explainability, fairness, and security.
Proven experience with LLMs such as Gemini, GPT, PaLM, or similar frameworks.
Hands-on experience in NLP and machine learning, including language model training, fine-tuning, and deployment.
Proficiency in Python and libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and LangChain.
Experience with cloud platforms like Google Cloud (Vertex AI), AWS, or Azure for deploying AI solutions.
Familiarity with MLOps tools for managing models in production environments.
Understanding of prompt engineering, embedding generation, and model evaluation metrics for LLMs.

Qualifications:

Bachelor’s or master’s degree in computer science, Information Technology, Engineering, or a related field.
Minimum overall 6 years of experience in the IT field with recent 4 years of relevant experience in Data Science.
Relevant certifications in programming languages, data technologies, or cloud platforms would be advantageous.

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Senior ML engineer

Factspan Overview:
Factspan is a pure play data and analytics services organization. We partner with fortune 500 enterprises to build an analytics centre 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 Bangalore, 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

➢ Selecting features, building, and optimizing classifiers/regression using machine
learning and deep learning techniques
➢ Proficient in using data analytics tools to perform queries and analyses and for defining
and correlating data, and skilled at utilizing data visualization platforms to organize
and present summarizations, predictive analysis, comparative analysis, dashboards, and
reporting.
➢ Processing, cleansing, and verifying the integrity of data used for analysis.
➢ Performing data mining and analytics to support ongoing continuous risk monitoring
and risk assessments of operational data to recognize patterns and trends, investigate
anomalies, and assess internal control environment.
➢ Utilize data analysis by leveraging various statistical techniques, and predictive
modeling to drive and identify indicators of risk
➢ Drive efficiency by automation of manual processes

More responsibilities in detail:
➢ Excellent understanding of machine learning algorithms, such as Random Forest,
Gradient Boosting, Naive Bayes, SVM, KNN. Good understanding of deep learning
algorithms, such as DNN, CNN, RNN, LSTM, Autoencoders.
➢ Deep Knowledge of ML/AI software and packages such as python: scikit-learn,
TensorFlow and R: CARET, PyTorch.
➢ Proficiency in statistics concepts: sampling theory, descriptive statistics, probability
distributions, statistical tests, dimensionality, reduction, Hypothesis testing, maximum
likelihood estimators, inference, etc.
➢ Expertise in model validation, hyperparameter tuning, and model selection techniques
such as cross validation, leave-one-out, bootstrap.
➢ Proficiency in using query languages such as SQL and spark.
➢ Services, Reporting Service, Power BI, Python, PySpark- Distributed Computing. Machine
Learning, Times Series, Data Mining, Mathematical, Modeling, Probability and Stochastic
Processes

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