Vice President

2 weeks ago

Mumbai, Maharashtra, India Kotak Life Insurance Full time

Overview:

Kotak Life Insurance invites applications for the role of Senior Lead- Model Development.

We are seeking a visionary leader with a robust expertise in model development, encompassing both traditional statistical methods and cutting-edge machine learning techniques.

This role is pivotal in our drive to transform data and analytics, elevating our modeling practices to new heights of innovation and efficiency in the life insurance sector.

Key Responsibilities:

  • Leadership in Model Development
  • Spearhead the development of advanced machine learning and predictive modeling strategies from scratch, enhancing business decisionmaking and customer experience.
  • Lead and mentor a team of talented data scientists and analysts in the design, construction, and deployment of diverse ML models.
  • Foster crossdepartmental collaboration to seamlessly integrate ML and predictive analytics into our core business processes.
  • Innovation and Strategic Planning
  • Keep abreast of the latest advancements in data science, machine learning, and insurtech, ensuring our strategies remain at the forefront of the industry.
  • Actively contribute to the strategic planning of the company's data and analytics initiatives.
  • Cultivate a datadriven culture within the organization, advocating for the power of analytics in every facet of our business.
  • Technical Expertise and Project Management
  • Offer expert guidance on a wide spectrum of statistical analysis, machine learning algorithms, and data modeling techniques.
  • Guarantee the accuracy, reliability, and integrity of our analytical solutions.
  • Efficiently manage and prioritize multiple projects, ensuring alignment with the company's strategic goals and deadlines.
  • Stakeholder Engagement and Communication
  • Provide direct and insightful reports to the Chief Data and Analytics Officer on project progress and strategic developments.
  • Collaborate closely with senior management to align data science solutions with business objectives.
  • Clearly articulate complex data and ML concepts to a nontechnical audience, ensuring transparency and understanding across the organization.
Core Skills & Capabilities:

  • Machine Learning: Demonstrable expertise in a specific area of machine learning.
  • Coding Proficiency: Exceptional skills in procedural languages such as Python, with practical experience in machine learning implementations. Familiarity with commandline tools.
  • Advanced Tool Knowledge: Experience with Hadoop ecosystem tools, largescale model deployment, and deep learning frameworks is highly advantageous.
Required Skills and Qualifications:

  • A minimum of 1015 years of experience in data science, with a significant focus on machine learning and predictive modeling.
  • A proven track record of leading and managing successful data science teams.
  • Comprehensive expertise in statistical analysis, machine learning techniques, and predictive modeling.
  • Proficiency in data science tools and programming languages including Python, R, SQL, and SAS Viya.
  • Exceptional problemsolving abilities and a strong analytical mindset.
  • Outstanding communication and leadership skills.
  • Bachelor's or Master's degree in Statistics, Econometrics, Computer Science, Data Science, or a related field. Experience in the insurance or BFSI sector is preferable.
Desired Attributes:

  • A strategic thinker passionate about innovation in data science and insurtech.
  • Ability to excel in a dynamic, fastpaced environment.
  • Strong interpersonal skills, adept at building relationships across various organizational levels.
  • Business acumen with a focus on delivering tangible value.
  • Skilled in communicating with nontechnical business stakeholders.
  • Committed to delivering business value, not just technical solutions.


What We Are Not Looking For:


  • Candidates with only core experience in standalone packages like SAS, SPSS, Cognos.
  • Professionals solely skilled in BI, business analysis, data engineering, ETL, analytics, or visualization without actual machine learning experience.
  • Programmers without a significant data track record, or data professionals without solid programming experience.
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