Senior Data Scientist

Job Role: Senior Data Scientist – AI/ML & Propensity Modeling

Location: Hyderabad

Experience: 8+ Years

About Anblicks

Anblicks is a Data & AI company helping global enterprises transform data into intelligent, scalable, and business-driven solutions. We specialize in Data Engineering, AI/ML, Cloud, Databricks, Snowflake, and Modern Data Platforms, delivering high-impact solutions for complex enterprise data and analytics challenges.

We are looking for a Senior Data Scientist to join our Data & AI team and lead the development of advanced machine learning, statistical modeling, predictive analytics, and AI solutions. This role is ideal for a hands-on Data Scientist who enjoys solving complex problems using large-scale data and building models that move from experimentation to production.

What You’ll Do

• • Design, develop, evaluate, and deploy advanced machine learning and statistical models for predictive analytics, propensity modeling, segmentation, and data products.
• Apply statistical modeling, machine learning, optimization, and AI techniques to solve complex business and analytical problems.
• Work with large and diverse datasets, including demographic, behavioral, transactional, digital, media, and other structured/unstructured data.
• Drive the complete data science lifecycle — data preparation, feature engineering, model development, validation, optimization, deployment, and monitoring.
• Build and optimize models using supervised and unsupervised learning, ensemble methods, deep learning, and advanced statistical techniques.
• Develop production-grade ML solutions using Python, PySpark, Spark MLlib, Scikit-learn, TensorFlow/Keras, or equivalent frameworks.
• Design and implement scalable ML pipelines using Spark/PySpark and cloud-based data/ML platforms.
• Build and maintain ETL, ML, and MLOps pipelines supporting reliable production deployment.
• Implement automated approaches for model validation, monitoring, QA, performance tracking, and model/drift monitoring.
• Work closely with Product, Engineering, Data Engineering, and Business teams to translate business objectives into scalable data science solutions.
• Define relevant KPIs and model performance metrics and communicate insights to technical and business stakeholders.
• Drive adoption of modern Cloud, AI/ML, Databricks, and MLOps technologies across data science initiatives.
• Explore and implement GenAI and AI Agent solutions to automate analytical and business workflows.
• Partner with engineering teams to successfully transition models and data science solutions from development to production.
• Present analytical findings, model performance, and recommendations to senior stakeholders and clients.
• Mentor junior Data Scientists and contribute to technical standards, best practices, and innovation initiatives.
• Required Skills & Experience
• • 8+ years of hands-on experience in Data Science, Machine Learning, Statistical Modeling, or a related field.
• Strong expertise in Python, with hands-on experience in Scikit-learn, Pandas, NumPy, and related data science libraries.
• Strong proficiency in SQL and experience working with large-scale datasets.
• Strong hands-on experience with Spark/PySpark and distributed data processing.
• Proven experience building, deploying, and optimizing production-grade machine learning models at scale.
• Strong understanding of:
• Regression & Classification
• Decision Trees & Random Forest
• Gradient Boosting / XGBoost
• SVM
• Clustering
• Dimensionality Reduction
• Neural Networks / Deep Learning
• Strong understanding of feature engineering, model training, hyperparameter tuning, model validation, performance evaluation, and optimization.
• 5+ years of experience building ETL, ML, data transformation, and/or MLOps pipelines.
• Hands-on experience with Databricks or other cloud-based ML/data platforms.
• Experience with Spark MLlib, Scikit-learn, TensorFlow, Keras, or equivalent ML frameworks.
• Strong understanding of MLOps and ML lifecycle management, including deployment, monitoring, versioning, automation, and model governance.
• 1–2+ years of experience with GenAI / AI Agents, using technologies such as Claude, Databricks Genie, Snowflake Cortex, LangChain, LangGraph, or similar platforms.
• Strong analytical and problem-solving capabilities with the ability to translate ambiguous business problems into practical, scalable ML solutions.
• Excellent communication and stakeholder management skills, with the ability to present complex analytical concepts clearly.
• Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline.

Good to Have

• • Experience in Propensity Modeling, Customer Analytics, Audience Analytics, Marketing Analytics, AdTech, or MarTech.
• Experience working with demographic, behavioral, survey, digital marketing, media, or transactional datasets.
• Hands-on experience with Databricks ML, MLflow, Unity Catalog, Feature Store, Mosaic AI, or similar platforms.
• Experience with Airflow, Kubeflow, or other workflow/orchestration platforms.
• Experience with H2O.ai or other AutoML platforms.
• Strong experience with Deep Learning / Neural Network frameworks, including TensorFlow and Keras.
• Exposure to LLMs, RAG, Agentic AI, Generative AI, and AI-powered automation.

What We’re Looking For

• • A hands-on and technically strong Data Scientist who can take ML solutions from concept to production.
• Strong ownership and a problem-solving mindset with a focus on measurable business impact.
• Ability to work with complex, imperfect, and large-scale datasets while maintaining analytical rigor.
• Passion for emerging AI/ML technologies and a strong desire to experiment, learn, and innovate.
• Ability to collaborate effectively with global, cross-functional, and client-facing teams.
• Strong focus on building scalable, reliable, production-ready AI/ML solutions.