
Gen AI
2 weeks ago
This role is responsible for managing the client expectations. Strategize with various stakeholders to meet customer requirements.
KEY RESPONSIBILITIES
- Data Science: Develop machine learning models to support recommendation systems and NLP projects; provide actionable insights for product and service optimization.
- Data Engineering: Build and maintain scalable ETL pipelines, optimize data storage solutions (data lakes, columnar formats), and ensure data accuracy for analytics.
- Data Analysis and Insight Generation: Skilled in analyzing complex datasets to uncover trends and patterns; generate and present insights that drive strategic decisions and enhance client services.
Stakeholder Collaboration: Work with product and service teams to understand data needs and translate them into technical solutions.
Technical Skills
- Proficiency with Python (Pandas, NumPy), SQL, and Java.
- Experience with LLMs, Lang Chain, and Generative AI technologies.
- Familiarity with ML frameworks (TensorFlow, PyTorch) and data engineering tools (Spark, Kafka).
- Microservices, CI CD, ML
- Strong data analysis skills and ability to present findings to both technical and non-technical stakeholders.
- Proficient understanding of key data engineering concepts, such as data lakes, columnar formats, ETL tools, and BI tools.
- Knowledge in Machine Learning, NLP, Recommender systems, personalization, Segmentation, microservices architecture and API development.
- Ability to adapt to a fast-paced, dynamic work environment and learn new technologies quickly.
Soft Skills
- Work in a team/ Independently.
- Excellent Written & Verbal Communication Skills
- Solid critical thinking and questioning skills.
- High degree of flexibility - willing to fill in the gaps rather than relying on others
- Strong communication skills, especially in presenting data insights.
Flexibility, problem-solving, and a proactive approach in a fast-paced environment .
Required Educational Qualification & Relevant
Experience
- Bachelors Degree in Computer Science, Data Analytics, Engineering, or a related field.
- Minimum of 3 to 5 years of experience in data science and data engineering.
- Strong critical thinking abilities and the capacity to work autonomously.
- Proficient understanding of key data engineering concepts, such as data lakes, columnar formats, ETL tools, and BI tools High motivation, good work ethic, maturity and personal initiative.
- Strong oral and written communication skills.
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