Lead / Manager Data Scientist at Blend360

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

08 Jan, 26

Salary

0.0

Posted On

10 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Pricing Optimization, Pricing Elasticity, AWS SageMaker, Bayesian Modeling, Machine Learning, Statistical Analysis, Python, R, Cloud Platforms, NumPy, Pandas, PyMC3, A/B Testing, Econometrics, Analytical Thinking

Industry

Professional Services

Description

Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com Job Description We are seeking a highly skilled Lead Data Scientist with experience in pricing optimization, pricing elasticity, and AWS SageMaker. The ideal candidate will have a strong foundation in Statistics and Machine Learning, with a particular focus on Bayesian modeling. As part of our Data Science team, you will work closely with clients to develop advanced pricing strategies using state-of-the-art tools and techniques, including AWS SageMaker, to optimize business outcomes. Key Responsibilities: Lead and contribute to the development of pricing optimization models, leveraging statistical and machine learning techniques to inform strategic decisions. Analyze pricing elasticity to predict consumer response to changes in price, helping clients maximize revenue and market share. Implement and deploy machine learning models using AWS SageMaker for scalable and efficient performance in a cloud environment. Utilize Bayesian modeling to support decision-making processes, providing insights into uncertainty and model predictions. Collaborate with cross-functional teams to integrate data-driven insights into business processes. Communicate complex results and findings in a clear and concise manner to both technical and non-technical stakeholders. Continuously explore and experiment with new modeling approaches and tools to improve accuracy and efficiency of pricing solutions. Qualifications Experience : 7 to 12 Years Bachelor’s or Master’s degree in Data Science, Statistics Mathematics Economics, or a related field. Advanced degrees preferred. 7+ years of hands-on experience in data science, with a focus on pricing optimization and elasticity modeling. Expertise in Bayesian modeling and machine learning techniques. Proven experience working with AWS SageMaker for model development, deployment, and monitoring. Familiarity with AWS Certified Data Analytics – Specialty certification is a plus. Strong programming skills in Python (preferred) or R. Experience with cloud platforms (AWS preferred), including SageMaker. Proficiency in statistical analysis tools and libraries (e.g., NumPy, Pandas, PyMC3, or similar) Excellent problem-solving and analytical thinking skills. Ability to work in a fast-paced environment and manage multiple projects. Strong communication skills with the ability to explain complex concepts to non-technical audiences. Preferred Qualifications: Experience with A/B testing, econometrics, or other statistical experimentation methods. Familiarity with other cloud computing platforms (e.g., Azure, GCP). Experience working in cross-functional teams and client-facing roles. Additional Information Opportunity to work with cutting-edge technology in a dynamic environment. Exposure to a diverse range of industries and projects. Collaborative and inclusive work culture with opportunities for growth and professional development.

Responsibilities

Lead the development of pricing optimization models and analyze pricing elasticity to inform strategic decisions. Collaborate with cross-functional teams to integrate data-driven insights into business processes.