Python Developer, Machine Learning

1 week ago

Mumbai, India HCLSoftware Full time

Role – Senior Python Developer (Data Science, AI/ML) HCL Software () delivers software that fulfills the transformative needs of clients around the world. We build award winning software across AI, Automation, Data & Analytics, Security and Cloud. Please share CV to ones will be invited for a virtual interview on 11th Oct Saturday The HCL Unica+ Marketing Platform enables our customers to deliver precision and high performance Marketing campaigns across multiple channels like Social Media, AdTech Platforms, Mobile Applications, Websites, etc. The Unica+ Marketing Platform is a Data and AI first platform that enables our clients to deliver hyper-personalized offers and messages for customer acquisition, product awareness and retention. We are seeking a Senior Python Developer with strong Data Science and Machine Learning skills and experience to deliver AI driven Marketing Campaigns. of Python Development Experience with at least 4 years in data science and machine learning # Experience with Customer Data Platforms (CDP) like TreasureData, Epsilon, Tealium, Adobe, Salesforce is advantageous. # Experience with AWS SageMaker is advantageous # Experience with LangChain, RAG for Generative AI is advantageous. # Knowledge of REST, JSON, XML, SOAP is a must # Ability to work well within an agile team environment and apply the related working methods. # A 4-year degree in Computer Science or IT is a must. Python Programming & Libraries: Proficient in Python with extensive experience using Pandas for data manipulation, NumPy for numerical operations, and Matplotlib/Seaborn for data visualization. # Statistical Analysis & Modelling: Strong understanding of statistical concepts, including descriptive statistics, inferential statistics, hypothesis testing, regression analysis, and time series analysis. # Data Cleaning & Preprocessing: Expertise in handling messy real-world data, including dealing with missing values, outliers, data normalization/standardization, feature engineering, and data transformation. # SQL & Database Management: Ability to query and manage data efficiently from relational databases using SQL, and ideally some familiarity with NoSQL databases. # Exploratory Data Analysis (EDA): Machine Learning Algorithms: In-depth knowledge and practical experience with a wide range of ML algorithms such as linear models, tree-based models (Random Forests, Gradient Boosting), SVMs, K-means, and dimensionality reduction techniques (PCA). # This includes understanding neural network architectures (CNNs, RNNs, Transformers) and their application to various problems. # precision, recall, F1-score, AUC-ROC, RMSE) for different problem types, diagnose model performance issues (bias-variance trade-off), and apply optimization techniques. # Deployment & MLOps Concepts: Understanding of how to deploy machine learning models into production environments, including concepts of API creation, containerization (Docker), version control for models, and monitoring. Travel: 30% +/- travel required

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