Adroitco Inc.
Engagement Type:
Full Time
Interview Rounds: 4
(Pre-Screening, Technical, Director, HR) Responsibilities:
As a Data Scientist, your role is pivotal in harnessing the power of data to derive actionable insights and contribute to our analytical initiatives. Key responsibilities include: Apply 5+ years of professional experience as a data engineer to design and implement robust data pipelines. Leverage Python and SQL for data processing, analysis, and modeling. Utilize expertise in state-of-the-art machine learning algorithms, including deep neural networks, support vector machines, boosting algorithms, and random forest. Apply advanced algorithms to extract meaningful patterns and insights from diverse datasets. Conduct advanced feature engineering to enhance model performance. Implement data dimension reduction techniques in a Big Data environment for improved efficiency. Demonstrate strong SQL skills in a Big Data environment, working with platforms like Hive and Impala. Conduct data analysis and extraction efficiently within large datasets. Technical Proficiency: Demonstrate proficiency in handling big data environments, showcasing a nuanced understanding of data complexities and scalability challenges. Apply expertise in conducting comprehensive analyses and generating insights. A Masters degree in computer science or data science, reflecting a strong academic foundation. Experience:
Showcase previous experience in notable sectors such as banking or e-commerce, bringing a nuanced understanding of industry-specific challenges and opportunities. #J-18808-Ljbffr
(Pre-Screening, Technical, Director, HR) Responsibilities:
As a Data Scientist, your role is pivotal in harnessing the power of data to derive actionable insights and contribute to our analytical initiatives. Key responsibilities include: Apply 5+ years of professional experience as a data engineer to design and implement robust data pipelines. Leverage Python and SQL for data processing, analysis, and modeling. Utilize expertise in state-of-the-art machine learning algorithms, including deep neural networks, support vector machines, boosting algorithms, and random forest. Apply advanced algorithms to extract meaningful patterns and insights from diverse datasets. Conduct advanced feature engineering to enhance model performance. Implement data dimension reduction techniques in a Big Data environment for improved efficiency. Demonstrate strong SQL skills in a Big Data environment, working with platforms like Hive and Impala. Conduct data analysis and extraction efficiently within large datasets. Technical Proficiency: Demonstrate proficiency in handling big data environments, showcasing a nuanced understanding of data complexities and scalability challenges. Apply expertise in conducting comprehensive analyses and generating insights. A Masters degree in computer science or data science, reflecting a strong academic foundation. Experience:
Showcase previous experience in notable sectors such as banking or e-commerce, bringing a nuanced understanding of industry-specific challenges and opportunities. #J-18808-Ljbffr