Datawrkz - Data Scientist - Machine Learning/Predictive Analytics

3 weeks ago


Delhi NCR, India Datawrkz Full time

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 skills

Responsibilities :


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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