Data Analyst - NLP/Machine Learning

Job Description : Roles and Responsibilities : - The Ideal candidate would act as Senior Consulting Engineer for Data Science and AI, will be responsible for doing design and development work on a daily basis, including but not restricted to Development, Deployment and Post Support of solutions using the entire Data and AI suite of products. - Design system architectures to meet the product needs and business scale both in the short and the long term. - Own the High-Level Design of systems and Low-Level Design of the domain in line with the industry standard practices to ensure ease of maintenance and iteration - Set goals for platform evolution, and the roadmap for achieving it. - Propose and drive technical innovation and experiments. - A minimum of 6-10 years of experience in Product Software Development is required. - Core competencies should include but not limited to Machine Learning, Deep Learning, Natural Language Processing, Data Mining, Data Engineering, Data Analysis & Data Visualization. - Expertise in programming in Java or Python. - Experience with various NLP/ML libraries in Python is an added advantage. - Design and Develop Content Moderation Models : Create and train models to automatically detect offensive language, hate speech, bullying, and other violations in user-generated content (UGC). - Implement Sentiment Analysis : Develop and refine models to gauge sentiment across user posts, comments, and reviews (e.g., positive, negative, joy, anger) to understand user engagement and flag potential issues. - Build Image and Video Moderation Models : Collaborate with computer vision specialists to detect explicit content in multimedia using models for nudity, violence, weapons, etc. - Monitor and Improve ACM Performance : Continuously evaluate moderation model effectiveness, minimize false positives/negatives, and update models as new types of content or trends emerge. - Collaborative Filtering & Content-Based Modeling : Develop personalized recommendation algorithms for flights, hotels, vacation rentals, etc., using collaborative filtering and content-based techniques. - Implement Hybrid Recommendation Systems : Combine multiple algorithms (e.g., matrix factorization, neural networks) for improved personalization. - A/B Testing and Personalization : Design experiments to validate the effectiveness of recommendations and improve user engagement metrics. - Optimize Real-Time Recommendation Delivery : Work with engineering to ensure recommendations are served in real time, meeting performance and scalability requirements. - Statistical Analysis and Predictive Modeling : Perform statistical analysis to uncover trends in booking behaviors, pricing, seasonal trends, and user preferences. - User Behavior Analysis : Track and analyze user journeys across the platform, identifying opportunities for product enhancement and improved customer experience. - Develop Dashboards and Reports : Provide actionable insights by building dashboards and reports for stakeholders using BI tools like Tableau or Power BI. - Market Segmentation and User Profiling : Implement clustering and classification techniques to segment users and tailor product offerings. - Collaborate with Data Engineering : Work closely with data engineers to establish scalable data pipelines for structured and unstructured data collection, preprocessing, and storage. - Model Deployment and Maintenance : Collaborate with ML Ops to deploy and monitor models in production environments, ensuring robustness and adaptability. - Data Quality and Compliance : Ensure data privacy, security, and regulatory compliance, especially with UGC and PII (Personally Identifiable Information). - Demand Forecasting : Build time series models to forecast demand for different regions, seasons, and services (e.g., hotels, flights). - Churn Prediction and Customer Retention Models : Identify at-risk users and offer insights for targeted engagement strategies. - Basic database / SQL experience. - A minimum of 3-5 years of experience in database application programming (SQL, PL/SQL and SQL PL). - Experience building software for SaaS and Continuous Delivery Techniques is desirable. - Demonstrates verbal and written communications skills. - Demonstrates strong analytical thinking and problem-solving skills. - Creative approach to problem solving, innovation and issue resolution. - Superior interpersonal skills and the ability to collaborate actively and proactively with others in a cross-functional team. Predictive Insights for Inventory Management: Work with business teams to forecast inventory needs based on demand patterns, booking trends, and external factors. Preferred Technical and Professional Expertise : - Machine Learning experience - Chatbots and NLP Application development experience - Demonstrates proactive communication skills and has collaboration experience. - Knowledge of the agile software development cycle - Knowledge of Online travel application/industry is an asset - Exceptional attention to detail, and a commitment to delivering under tight time constraints Mandatory Skills : - Statistical Analysis and Hypothesis Testing: Proficiency in statistical methods, hypothesis testing, and experiment design (e.g., A/B testing). - Machine Learning: Solid understanding of algorithms including classification, clustering, regression, and deep learning; experience with frameworks like Scikit-Learn, TensorFlow, or PyTorch. - NLP and Sentiment Analysis : Strong skills in Natural Language Processing (NLP) for text analysis, sentiment analysis, and content moderation tasks, using libraries such as NLTK, SpaCy, or transformers like BERT. - Recommendation Algorithms : Familiarity with collaborative filtering, content-based filtering, matrix factorization, and hybrid recommendation systems. - Time Series Analysis : Experience with time series forecasting techniques like ARIMA, Prophet, or LSTM for demand and price prediction. - Data Preprocessing and ETL Pipelines : Proficiency in data wrangling, cleaning, and transformation; experience with tools like Apache Spark, Airflow, or NiFi is a plus. - Database Knowledge : Strong understanding of SQL and familiarity with NoSQL databases (e.g., MongoDB, Elasticsearch) for handling large-scale UGC. - Big Data and Cloud Platforms : Experience working with big data technologies (Hadoop, Hive) and cloud environments (AWS, GCP, or Azure). - Data Visualization Tools : Proficiency with visualization tools such as Tableau, Power BI, or matplotlib/seaborn for presenting insights. - Dashboard Development : Experience building and maintaining data dashboards and reports for cross-functional teams. - Model Deployment and ML Ops : Knowledge of deploying models in production environments, using Docker, Kubernetes, or ML Ops tools like MLflow or TFX. - APIs and Real-Time Data Processing : Experience building APIs to serve models or integrate recommendations; knowledge of Kafka or RabbitMQ for streaming data. - Problem Solving and Critical Thinking : Ability to translate business needs into data science problems and develop effective solutions. - Collaboration and Communication : Strong communication skills for collaborating with cross-functional teams, including engineering, product, and marketing teams, and the ability to explain complex models to non-technical stakeholders. (ref:hirist.tech)

Location: delhi, IN

Posted Date: 11/22/2024