Datawrkz
Location
Delhi | India
Job description
Key Responsibilities :- Lead a team of software developers, including hiring, training and mentoring.- Provide technical guidance and direction to the team, including coding standards, architectural.- Principles, and development best practices, including appropriate documentation and review.- Collaborate with the Product Manager and other stakeholders to define project requirements, scope, and timelines.- Participate in the design and development of software solutions, ensuring they meet quality and performance standards.- Monitor project progress, identify and mitigate risks, and communicate project status to stakeholders.- Identify technical debt and provide recommendations to address it.- Evaluate new technologies and tools, and recommend their adoption where appropriate.- Foster a culture of continuous improvement, innovation, and collaboration within the team.Skills and Experience :- Bachelor's or Master's degree in Computer Science or related field.- 4+ years of experience in software development, with a focus on backend or full-stack development.- 2+ years of project management experience, leading a team of software developers.- Strong experience with Python, Django or other frameworks.- Experience with web development frameworks such as React,Angular.- Experience with cloud based solutions, deployment etc.- Experience with Agile development methodologies, such as Scrum or Kanban.- Strong communication and leadership skills.- Strong problem-solving and analytical skillsResponsibilities : Data Analysis and Modeling : - Conduct exploratory data analysis to identify trends, patterns, and insights. - Develop and implement machine learning models and algorithms for predictive and prescriptive analytics. - Utilize statistical methods to extract meaningful information from large datasets. Data Cleaning and Preprocessing : - Clean, preprocess, and validate raw data to ensure accuracy and completeness. - Handle missing data and outliers, and implement strategies for data imputation. Feature Engineering : Identify relevant features and engineer new ones to enhance model performance. Collaborate with domain experts to incorporate domain knowledge into feature selection. Model Evaluation and Optimization : Evaluate model performance using appropriate metrics. Fine-tune models and algorithms to improve accuracy, precision, and recall. Data Visualization : Create visualizations to communicate complex findings and results effectively. Use tools such as Matplotlib, Seaborn, or Tableau for data visualization. Collaboration : Work closely with cross-functional teams, including business stakeholders, to understand business objectives and requirements. Communicate findings and insights to non-technical stakeholders in a clear and understandable manner. Research and Development : Stay updated on the latest developments in data science and machine learning. Contribute to the research and development of new algorithms and methodologies. Data Privacy and Ethics : Ensure compliance with data privacy regulations and ethical considerations in handling sensitive information. (ref:hirist.tech)
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