Data Scientist - Time Series

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As a Data Scientist, your work is a combination of hands-on contribution to Loreum Ipsum, Loreum Ipsum, etc. More specifically, this will involve: Lead and contribute to developing sophisticated machine learning models, predictive analytics, and statistical analyses to solve complex business problems.

• Demonstrate proficiency in programming languages such as Python or R, with the ability to write clean, efficient, and maintainable code. Experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) is essential.
• Use your robust problem-solving skills to develop data-driven solutions, analyse complex datasets, and derive actionable insights that lead to impactful outcomes.
• Work closely with clients to understand their business objectives, identify opportunities for analytics-driven solutions, and communicate findings clearly and promptly.
• Take ownership of end-to-end model development, from problem definition and data exploration to model training, validation, and deployment.
• Collaborate with cross-functional teams, including data engineers, software developers, and business stakeholders, to integrate analytics solutions into business processes. Leverage a profound understanding of mathematical and statistical principles to guide and validating advanced data science models.
• Stay abreast of industry trends, emerging technologies, and best practices in data science, bringing innovative ideas to the team and contributing to continuous improvement.

Preferred candidate profile

• 4 -6 years of total DS and model development experience A. passion for writing high-quality code (Python), and the code should be modular, scalable, and end-end project execution while planning an active hands-on role

• Having good problem-solving skills is essential, and it is equally important to have in-depth knowledge to solve complex problems effectively. •
• Comprehensive knowledge of the regression and classification concepts and mathematical backend along with SQL
• Experience in

  Time Series Forecasting (Mandate)

• Idea about other machine learning techniques (clustering, regression, ensemble learning, neural nets, time series, optimizations etc,.) to their real-world problems •
• Encourage collaboration with various stakeholders and take complete ownership of deliverables.
• Adept understanding of various data science approaches, machine learning algorithms, and statistical methods. Excellent communication skills with presentability, articulation, storytelling capability, and ability to manage complex client situations •
• Effective mentoring of a team with expertise in industry/domain/functional areas.