Shyam
ML EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Lead Data Scientist | AI Architect — Enterprise GenAI & Agentic Systems | Machine Learning | 10.8+ Yrs Exp
I am a 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗔𝗜 𝗟𝗲𝗮𝗱𝗲𝗿 with 10+ years of experience architecting and operating 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝘀𝗰𝗮𝗹𝗲 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀 and Solutions. My core focus is transforming AI from experimental prototypes into 𝗵𝗶𝗴𝗵-𝗰𝗼𝗻𝗰𝘂𝗿𝗿𝗲𝗻𝗰𝘆, 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲-𝗴𝗿𝗮𝗱𝗲 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 that deliver measurable business outcomes. I specialize in building systems that balance 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲, 𝘀𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆, 𝗮𝗻𝗱 𝗰𝗼𝘀𝘁-𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆, ensuring AI initiatives translate into real-world impact—not just innovation for its own sake. 💡 𝗪𝗵𝗮𝘁 𝗜 𝗕𝗿𝗶𝗻𝗴 ● 𝗣𝗿𝗼𝘃𝗲𝗻 𝗥𝗢𝗜: Delivered over $𝟬.𝟮𝟱𝗠 𝗶𝗻 𝗮𝗻𝗻𝘂𝗮𝗹𝗶𝘇𝗲𝗱 𝘀𝗮𝘃𝗶𝗻𝗴𝘀 by optimizing AI unit economics and reducing inference costs. ● 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻: Led the shift from monolithic ML systems to 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲𝘀 (𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵), increasing feature deployment velocity by 𝟯𝟱%. ● 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲-𝗦𝗰𝗮𝗹𝗲 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: Designed platforms supporting 𝘁𝗵𝗼𝘂𝘀𝗮𝗻𝗱𝘀 𝗼𝗳 𝗱𝗮𝗶𝗹𝘆 𝗶𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 while maintaining 𝗣𝟵𝟱 𝗹𝗮𝘁𝗲𝗻𝗰𝘆 ≤ 𝟱𝟬𝟬𝟬𝗺𝘀 for complex reasoning workflows . ● 𝗟
International School of Engineering (INSOFE)
Postgraduate Degree, Big Data Analytics and Optimization
March 1, 2017 – September 1, 2017
Netaji Subhash Engineering College (NSEC)
Bachelor of Technology (BTech), Information Technology
January 1, 2011 – January 1, 2015
ADP
Lead Data Scientist
August 1, 2023 – Present
ValueMomentum
Senior Data Scientist (SSE-ML)
October 1, 2018 – July 1, 2023
CENTILLION NETWORKS
AI Scientist
February 1, 2018 – September 1, 2018
Tata Consultancy Services
SE (ML)
August 1, 2015 – January 1, 2018
Cultural Fit Analysis
The candidate has a consistent career progression in Data Science and ML Engineering roles across different companies, indicating adaptability and a commitment to the field. The projects described involve diverse applications of ML, including NLP, Computer Vision, and autonomous systems, which suggests a broad interest and ability to work on varied challenges. The focus on enterprise-level solutions and optimization aligns with a culture that values impact and efficiency. However, the lack of explicit project details beyond work experience makes it harder to assess collaboration styles or community involvement.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight a strong focus on problem-solving, optimization, and automation, indicating a proactive and results-oriented approach. The emphasis on improving metrics like cost-per-inference, MTTR, and accuracy suggests a strong operational fit for roles requiring continuous improvement and efficiency. The detailed descriptions of impact (e.g., 'reduced cost-per-inference by 45%', 'improved document processing accuracy by 45%') suggest a data-driven mindset.