Optimization Specialist

Job Description

JD Optimization Specialist Job Summary: We are seeking an experienced Data Scientist with a strong background in optimization to join our team. The ideal candidate will have 12-17 years of experience in data science, machine learning, optimization techniques and Gen AI. This role involves leading complex data science and Gen AI projects ( with a focus in solving optimization problems), mentoring junior data scientists, and driving data-driven decision-making. Roles and Responsibilities: 12-17 years of overall experience in the design, implementation, or consulting within the data science and AI space. Oversee the design, development, and implementation of advanced optimization models to solve complex business problems, across domains ( manufacturing, hitech, retail , oil & gas, etc.) Apply optimization techniques such as linear programming, integer programming, mixed integer linear programming, nonlinear optimization, and heuristic and meta heuristic algorithms ( like Genetic Algorithms ) to solve business problems. Analyzing and understanding use cases to verify their fitment and to determine the best solution approach for data science and generative AI applications. Work closely with cross-functional teams including pre-sales, sales, hyper scalar platforms, to integrate the AI solutions and drive business outcomes Documenting comprehensive technical artifacts and establishing best practices for implementing and deploying AI models on various cloud platforms. Leading a team of leads and developers in building Proof of Concepts (POCs) for various customers. Provide guidance and mentorship to junior data scientists, and sharing knowledge in data science, optimization and AI technologies, fostering a culture of continuous learning and improvements Ensuring AI solutions adhere to quality and ethical standards while optimizing their performance in production for reliability and efficiency. Technical Skills Proficiency in optimization tools, libraries & products such as CPLEX, Gurobi, PuLP, Llamasoft, etc. Experience with building and implementing optimization techniques like linear programming, Mixed Integer Linear Programming, nonlinear optimization, Genetic Algorithms, and heuristic and meta – heuristic algorithms. Proficiency in programming languages like Python, R, and SQL. Expertise in data manipulation and analysis using libraries such as Pandas, NumPy, and Scikit-learn, SciPy Strong experience with machine learning frameworks like TensorFlow, Keras, and PyTorch Proficiency in using LLM, and LLM – based frameworks like RAG, agentic framework to develop AI solutions Strong communication skills and experience in managing various stakeholder relationships to gain consensus on complex technical solutions. Deep experience in architecting, designing, and implementing solutions on-premises, in the cloud, and using hybrid models, and mastery of the latest AI frameworks. In-depth experience in fine-tuning and customizing pretrained LLMs and AI models, with good understanding of various patterns and practices in AI, data engineering, and large data processing. Proficiency with a variety of tools and platforms, including but not limited to Amazon SageMaker, Azure ML Studio, Azure Data Lake, Google BigQuery, Vertex AI, AWS S3, Databricks and Snowflake. Experience with relational and non-relational databases (e.g., MySQL, MongoDB). Relevant certifications in data science, optimization, operations research, Gen AI at the Architect/Lead level will be an advantage. Behavioral Skills: Excellent verbal and written communication skills to articulate complex data insights to non-technical stakeholders. Problem-Solving: Strong analytical and problem-solving abilities to tackle challenging data and optimization issues. Collaboration: Ability to work effectively in a collaborative environment and build strong relationships with cross-functional teams. Adaptability: Flexibility to adapt to changing business needs and technological advancements. Attention to Detail: High level of attention to detail and commitment to delivering high-quality work. Other Skills: Project Management: Experience in managing large-scale data science, optimization and Gen AI projects and ensuring timely delivery. Business Acumen: Understanding of business processes and the ability to align data science, optimization and AI initiatives with organizational goals.