Python Developer with AIML

Role – Senior Python Developer (Data Science, AI/ML)

HCL Software (
hcl-
) 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 - with the below details:

Current CTC-

Expected CTC-

Notice Period-

Shortlisted 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.

Qualifications & Skills

1. At least 8-10 years. of
   Python
   Development Experience with at least 4 years in data science and machine learning
2. Experience with Customer Data Platforms (CDP) like TreasureData, Epsilon, Tealium, Adobe, Salesforce is advantageous.
3. Experience with AWS SageMaker is advantageous
4. Experience with LangChain, RAG for Generative AI is advantageous.
5. Expertise in Integration tools and frameworks like Postman, Swagger, API Gateways
6. Knowledge of REST, JSON, XML, SOAP is a must
7. Ability to work well within an agile team environment and apply the related working methods.
8. Excellent communication & interpersonal skills
9. A 4-year degree in Computer Science or IT is a must.

Responsibilities

1. Python Programming & Libraries: Proficient in Python with extensive experience using Pandas for data manipulation, NumPy for numerical operations, and Matplotlib/Seaborn for data visualization.
2. Statistical Analysis & Modelling: Strong understanding of statistical concepts, including descriptive statistics, inferential statistics, hypothesis testing, regression analysis, and time series analysis.
3. Data Cleaning & Preprocessing: Expertise in handling messy real-world data, including dealing with missing values, outliers, data normalization/standardization, feature engineering, and data transformation.
4. SQL & Database Management: Ability to query and manage data efficiently from relational databases using SQL, and ideally some familiarity with NoSQL databases.
5. Exploratory Data Analysis (EDA): Skill in visually and numerically exploring datasets to understand their characteristics, identify patterns, anomalies, and relationships.
6. 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).
7. Deep Learning Frameworks: Proficiency with at least one major deep learning framework like TensorFlow or PyTorch. This includes understanding neural network architectures (CNNs, RNNs, Transformers) and their application to various problems.
8. Model Evaluation & Optimization: Ability to select appropriate evaluation metrics (e.g., precision, recall, F1-score, AUC-ROC, RMSE) for different problem types, diagnose model performance issues (bias-variance trade-off), and apply optimization techniques.
9. 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

Location:
India (Pune preferred)