Data Science Engineer

TENARAI TECHNOLOGIES PRIVATE LIMITED; Gurugram District; On-site; INR 2,600,000 - 3,800,000; Full time

Job summary

TENARAI TECHNOLOGIES PRIVATE LIMITED is seeking a Data Science & AI Engineer with Big Data specialization in Gurgaon. Proficiency in Python and SQL is essential, with knowledge of Scala/Java a plus.

The role emphasizes AI/ML tools, cloud platforms, and big data technologies. You will architect and deploy scalable AI/ML solutions, design data pipelines, and collaborate with cross-functional teams to translate business needs into analytics.

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.
• Big Data experience with Hadoop, Spark, Hive, Kafka.
• Familiarity with cloud Big Data services (AWS, GCP, Azure).
• Experience with data visualization tools (Power BI/Tableau).
• Knowledge of NLP/Computer Vision is a plus.
• Excellent communication and collaboration skills.

Responsibilities

• Develop AI/ML models and scalable algorithms for large data sets.
• Architect and deploy robust AI/ML solutions in production.
• Collaborate with cross-functional teams to translate business needs into analytics.
• Stay updated with AI/ML and Big Data trends and apply them.
• Design efficient data pipelines for ingestion and processing at scale.
• Contribute to Big Data infra, ensuring reliability and performance.
• Communicate insights through clear visualizations and narratives.
• Mentor junior team members and foster knowledge sharing.

Skills

Python

SQL

Scala/Java

Analytical thinking

Problem solving

Communication skills

Git

Agile methodologies

Education

Bachelor’s or Master in CS/Data Science/Engineering

Statistics/Mathematics background

AI/DS/Big Data/Cloud certifications (plus)

Tools

TensorFlow

PyTorch

Scikit-learn

Spark MLlib

Hadoop

Spark

Hive

Kafka

Power BI

Tableau

Job description

Location: Gurgaon

Job Summary:

Data Science & AI Engineer - Big Data Specialization - 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.

Job Description:

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 or Master 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.