Job
Description
In this role, you will be responsible for working on various aspects of Data Science, Data Engineering, Data Analysis & Insight Generation, Stakeholder Collaboration, and building working relationships with different teams. Your key responsibilities will include: - Developing machine learning models to support recommendation systems and NLP projects - Providing actionable insights for product and service optimization - Building and maintaining scalable ETL pipelines - Optimizing data storage solutions (data lakes, columnar formats) and ensuring data accuracy for analytics - Analyzing complex datasets to uncover trends and patterns - Generating and presenting insights that drive strategic decisions and enhance client services - Collaborating with product and service teams to understand data needs and translate them into technical solutions You should possess the following skills and competencies: Technical Skills: - Proficiency with Python (Pandas, NumPy), SQL, and Java - Experience with LLMs, Lang Chain, and Generative AI technologies - Familiarity with ML frameworks (Tensor Flow, PyTorch) and data engineering tools (Spark, Kafka) - Strong data analysis skills and ability to present findings to both technical and non-technical stakeholders - Proficient in 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 quickly learn new technologies Soft Skills: - Working well in a team or independently - Excellent written & verbal communication skills - Strong 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 You are required to have the following academic qualifications and experience: - Bachelor's Degree in Computer Science, Data Analytics, Engineering, or a related field - Minimum 3 to 5 years of experience in data science and data engineering - Strong critical thinking abilities and capacity to work autonomously - Proficient understanding of key data engineering concepts (data lakes, columnar formats, ETL tools, and BI tools) - High motivation, good work ethic, maturity, and personal initiative - Strong oral and written communication skills In this role, you will be responsible for working on various aspects of Data Science, Data Engineering, Data Analysis & Insight Generation, Stakeholder Collaboration, and building working relationships with different teams. Your key responsibilities will include: - Developing machine learning models to support recommendation systems and NLP projects - Providing actionable insights for product and service optimization - Building and maintaining scalable ETL pipelines - Optimizing data storage solutions (data lakes, columnar formats) and ensuring data accuracy for analytics - Analyzing complex datasets to uncover trends and patterns - Generating and presenting insights that drive strategic decisions and enhance client services - Collaborating with product and service teams to understand data needs and translate them into technical solutions You should possess the following skills and competencies: Technical Skills: - Proficiency with Python (Pandas, NumPy), SQL, and Java - Experience with LLMs, Lang Chain, and Generative AI technologies - Familiarity with ML frameworks (Tensor Flow, PyTorch) and data engineering tools (Spark, Kafka) - Strong data analysis skills and ability to present findings to both technical and non-technical stakeholders - Proficient in 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 quickly learn new technologies Soft Skills: - Working well in a team or independently - Excellent written & verbal communication skills - Strong 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 You are required to have the following academic qualifications and experience: - Bachelor's Degree in Computer Science, Data Analytics, Engineering, or a related field - Minimum 3 to 5 years of experience in data science and data engineering - Strong critical thinking abilities and capacity to work autonomously - Proficient understanding of key data engineering concepts (data lakes, columnar formats, ETL tools, and BI tools) - High motiva
