Immediate joiners only - 15 to 20days max
Job Title: Data Science & AI Engineer - Big Data Specialization
Location: Noida / Gurgaon Type: Full Time Experience Level: 5-8 Years
About the Role:
Are you a highly motivated Data Science and AI Engineer passionate about tackling complex challenges with cutting-edge technologies We are seeking a talented individual to join our innovative team and contribute to the development of impactful solutions within the Mobile, Consumer Goods, and Apparel industries.
In this pivotal role, you will leverage your deep expertise in advanced data science techniques and AI/ML methodologies, with a strong emphasis on handling and processing large-scale datasets. You will be instrumental in driving data-driven decisions and building intelligent systems that directly impact our business. Your contributions will span the entire lifecycle of AI/ML projects, from ideation to deployment and continuous improvement.
In this role, you will:
- Extract actionable insights from complex, large-scale datasets using advanced analytical and statistical methods.
- Architect, develop, and deploy scalable and robust AI/ML solutions that address critical business needs and drive tangible value.
- Collaborate effectively with cross-functional teams including business stakeholders, product managers, and engineering teams to translate business requirements into impactful AI/ML initiatives.
- Stay at the forefront of advancements in data science, AI, and Big Data technologies, proactively exploring and integrating new methodologies and tools.
- Design and implement efficient data pipelines for data ingestion, processing, and storage, optimized for large volumes and real-time capabilities.
- Contribute to the development of our Big Data infrastructure and ensure its scalability, reliability, and performance.
- Communicate complex technical findings and insights effectively to both technical and non-technical audiences through clear visualizations and compelling narratives.
- Mentor and guide junior team members, fostering a collaborative and knowledge-sharing environment.
Key Responsibilities:
- AI/ML Model Development: Design, develop, and deploy predictive models and algorithms to solve real-world business challenges, with a focus on scalability and performance within a Big Data environment.
- Data Analytics & Exploration: Process large datasets to discover critical patterns, correlations, and actionable insights, utilizing Big Data processing frameworks and tools.
- Experimentation & Validation: Conduct rigorous A/B testing, hyperparameter tuning, and cross-validation to optimize models and ensure their robustness and generalizability.
- AI Tools & Platforms (Big Data Focus): Integrate models with cloud platforms (GCP, AWS, or Azure) and deploy AI/ML models in production systems, leveraging Big Data services and infrastructure.
- Research & Innovation: Stay updated with the latest advancements in AI, NLP, and machine learning, with a particular emphasis on Big Data applications and emerging trends.
- Big Data Infrastructure & Pipelines: Design, build, and maintain scalable data pipelines using technologies like Spark, Hadoop, Kafka, and cloud-based data warehousing solutions.
- Performance Optimization: Optimize AI/ML models and data processing pipelines for performance, efficiency, and scalability within a Big Data context.
- Monitoring & Maintenance: Implement robust monitoring systems to track model performance and ensure the reliability and stability of deployed AI/ML solutions in production.
Required Skills & Qualifications:
- Proficiency in Programming: Python and SQL are essential. Experience with other languages like Scala or Java is a plus.
- Strong Expertise in AI/ML Tools: TensorFlow, PyTorch, Scikit-learn, and similar frameworks are crucial. Experience with Big Data ML libraries (e.g., Spark MLlib) is highly desirable.
- Big Data Expertise: Proven experience working with distributed computing systems and Big Data technologies such as Hadoop, Spark, Hive, and Kafka. Familiarity with cloud-based Big Data services (e.g., AWS EMR, Google Cloud Dataproc, Azure HDInsight) is a significant advantage.
- Cloud Platforms: Familiarity with Google Cloud Platform (preferred), AWS, and/or Azure for model deployment and data pipelines, with a focus on their Big Data and AI/ML services.
- Data Visualization Skills: Experience with Power BI, Tableau, or similar tools to effectively communicate data insights.
- Knowledge of NLP/Computer Vision: Hands-on experience in Natural Language Processing or Image Recognition methodologies is a plus, especially in the context of large datasets.
- Analytical Thinking & Problem Solving: Ability to translate complex business problems into analytical frameworks and develop data-driven solutions within a Big Data environment.
- Excellent Communication Skills: Strong ability to collaborate across teams and communicate insights effectively, including presenting technical concepts to non-technical stakeholders.
- **Strong understanding of data modeling, data warehousing concepts, and ETL processes, particularly in the context of Big Data.
- **Experience with version control systems (e.g., Git).
- Understanding of software development best practices and agile methodologies.
Preferred Experience:
- 5-8 years of hands-on experience in Data Science or AI/ML roles, with a significant focus on Big Data projects.
- Experience in industries like Mobile, Consumer Goods, or Apparel is a strong plus.
- Exposure to working in Agile/Scrum environments.
- Experience with MLOps practices and tools for automating and scaling ML workflows.
- Contributions to open-source projects or a strong portfolio showcasing Big Data and AI/ML projects.
Educational Requirements:
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related field with a strong quantitative focus.
- Certifications in AI, Data Science, Big Data, or Cloud Technologies are a plus.
