Job Details

Data Science Practice Lead at Suyati Technologies

Suyati Technologies

Suyati Technologies

Job Location




Work Experience

5 Years - 10+ Years

Required Qualifications

Bachelor of Engineering / Bachelor of Technology / M. Tech / Master of Engineering /

Job Description

Suyati is hiring leaders with a high degree of experience in Client Management, Delivery Management, Technology Management, Financial Management and Team Management. 

About the company

Founded in 2009, Suyati Technologies partners with clients to engineer great experiences for digital customers. We collaborate with businesses to strategize and implement impactful digital initiatives that position our clients ahead of the competition. We are digital-first and focus on delivering great customer experiences that accelerate exponential growth. Our approach to customer experience can be summed up in one phrase – Buyer Rhythms (BR). BR is the deep understanding of your customer by focusing on and learning from the repeated patterns they create while interacting with your business. It offers you detailed insights, delivered in a seamless manner within your existing IT ecosystem.

With our niche and rich expertise in CMS, CRM, e-commerce and Marketing Automation, we help companies across the globe leverage their best on web and cloud through our platform integration, data analytics and customer engagement services.

Key Responsibilities

  1. Set up CoE and business practice for Enterprise AI solutions.
  2. We are setting up Data Science & Analytics as a Service - DaaS
  3. Build a practice with capabilities to  A) Create solution blueprints and roadmaps B) Orchestrate data acquisition, management and engineering C) Build AI/ML models to solve analytical problems
  4. Keeping up-to-date with industry trends and developments
  5. Promote Collaboration and Engagement
  6. Create technical POCs & solution demos
  7. Drive discussions across internal and external stakeholders to evaluate and design AI/ML solutions to support pre-sales, opportunity qualification, digital consulting and implementation engagements.
  8. Implement framework across solutions development lifecycle phases like opportunity qualification, maturity assessment, solution design, implementation, maintenance and scaling of solution.
  9. Develop value tracking mechanism to track ROI for AI/ML projects
  10. Hiring, Training and Mentoring a team of AI/ML experts as part of delivery teams for creating technical solutions based on AI/ML products and platform
  11. Keeping up-to-date with industry trends and developments
  12. Promote Collaboration and Engagement
  13. Create technical POCs & solution demos

Technical Skills (Must Have)

5+ years of relevant AI-ML experience with good exposure to agile software development methodology.

  1. Must have worked on at-least two large big-data projects and/or data-driven decision making projects involving data engineering, analytics and data science. (Advanced)

  2. Expertise in the tools and techniques involving data preparation, movement and analysis of data - including visualization, machine learning and NLP. (Advanced)

  3. Fair understanding of at least one of the following verticals - by virtue of solving data science problems in that domain: Insurance, Manufacturing, and Education. (Advanced)

  4. Expertise in AI/ML enabled solution development and implementation leveraging high volume and high-velocity data across disparate systems. (Advanced)

  5. Expertise in developing and supporting very large-scale Enterprise analytical solutions. (Advanced)

  6. Vision and ability to set up solution practice groups. (Intermediate)

  7. Statistical modelling, ML Techniques and concepts. (Advanced)

Technical Skills (Good to Have)

  1. Spark/ Spark MLlib - Years of Experience - 1+. Level - (Intermediate)
  2. Visualization tools - Tableau/Power BI/Qlik View - Years of Experience - 1+. Level - (Intermediate)

  3. Cloud - Azure ML/AWSSageaker /Snowflake - Years of Experience - 1+. Level - (Intermediate)

  4. ML Ops - Years of Experience - 1+. Level - (Intermediate)

  5. Automated ML - Years of Experience - 1+. Level - (Intermediate)
  6. NLP and Image/Video Analytics - Years of Experience - 2+. Level - (Intermediate)

Non - Technical Skills (Must Have)

  1. A master’s degree in Mathematics, Statistics, Machine Learning, Big Data Analytics, Computer Sciences or equivalent. (Expert)

  2. Possess excellent interpersonal and people skills. Able to work with a predominantly remote workforce. (Expert)

  3. Should have an analytical mindset and good debugging skills. (Expert)

  4. Possess excellent verbal and written English communication skills as necessary for a leader. (Expert)


Any Data Science certification.

Required Skills

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