Sr Manager Caregiver experience
What will you be responsible for?
- Lead the development and implementation of advanced analytics projects to address business challenges and opportunities.
- Develop and deploy predictive models by doing research work for right model, data preparation involving various databases, building model and finetuning for accuracy and integrating with business application efficiently to optimize business processes and improve customer experience.
- Design and build machine learning models to extract insights from large datasets and improve decision-making processes.
- Collaborate with cross-functional teams including data engineers, business analysts, and product managers to define project requirements and deliver actionable insights.
- Conduct exploratory data analysis to identify trends, patterns, and outliers in data, and communicate findings to stakeholders.
- Stay current with industry trends and advancements in machine learning and data science techniques and provide recommendations for adopting new technologies and methodologies.
- Mentor junior data scientists and provide guidance on best practices for data analysis, model development, and presentation of results.
- Work closely with stakeholders to understand business objectives and develop data-driven solutions to address their needs. Communicate complex technical concepts and findings to non-technical stakeholders in a clear and concise manner.
- Lead by example in fostering a culture of innovation, collaboration, and continuous learning within the data science team.
What would your day look like?
- Deploying analytics solutions and enabling tracking of business outcomes.
- Responsible for ML model architecture design.
- Project management, mentoring Junior members in the team and Client Interaction.
- Ensuring Quality through compliance to framework, architecture and coding standards.
- Selecting features, building and optimizing classifiers using machine learning techniques.
- Leading the team in an agile way
- Cross collaboration with other business verticals
Who are we looking for?
- 12 to 18 years of demonstrated experience in providing enterprise data solutions, by reporting and predictive analytics models.
- Expertise in Python, R, Data bricks, SAS.
- Expertise in applied statistics skills, such as distributions, statistical testing, regression, supervised and un-supervised ML models, NLP, Deep learning concepts.
- Experience in Data warehousing concepts
- Experience in any BI tools like Power BI, Tableau, Qlik
- Relevant work experience in data Science/advanced programming and in data engineering practice and platforms
Experience with Cloud based platforms like Google Cloud, AWS, Azure services used for data storage and data ingestion/ transformation and analytics.
- Building and implementing models, algorithms and simulations and executing the same using a variety of tools
- Very good scripting and programming skills necessary to build and efficient and streamlined process/environment
- Code Versioning Tool - GitHub
- Experience in relational and NoSQL Databases
- Knowledge on Agile methodology (JIRA, DevOps)
- B.E. in Computer Science, Information systems, or Computer engineering, Systems Engineering or M.S. in Statistics
- IT Infrastructure domain knowledge is preferred.
- Mathematics and Statistical background are preferred