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About the Role

We are looking for a highly skilled Machine Learning Lead with proven expertise in demand forecasting to join our team. The ideal candidate will have 4-8 years of experience building and deploying ML models, strong knowledge of AWS ML services and MLOps practices, and the ability to lead a team while working directly with clients. This is a client-facing role that requires strong communication skills, technical depth, and leadership ability.

Key Responsibilities

• Lead end-to-end design, development, and deployment of demand forecasting models.
• Collaborate with clients to gather requirements, define KPIs, and translate business needs into ML solutions.
• Architect and implement ML workflows using AWS ML ecosystem (SageMaker, Bedrock, Lambda, S3, Step Functions, etc.).
• Establish and enforce MLOps best practices for scalable, reproducible, and automated model deployment and monitoring.
• Mentor and guide a team of ML engineers and data scientists, ensuring technical excellence and timely delivery.
• Partner with cross-functional teams (engineering, data, business) to integrate forecasting insights into client systems.
• Present results, methodologies, and recommendations to both technical and non-technical stakeholders.
• Stay updated with the latest advancements in forecasting algorithms, time-series modeling, and AWS ML offerings.

Required Skills & Experience

• 4-8 years of experience in machine learning with a strong focus on time-series forecasting and demand prediction.
• Hands-on experience with AWS ML stack (Amazon SageMaker, Step Functions, Lambda, S3, Athena, CloudWatch, etc.).
• Strong understanding of MLOps pipelines (CI/CD for ML, model monitoring, retraining workflows).
• Proficiency in Python, SQL, and ML libraries (TensorFlow, PyTorch, Scikit-learn, Prophet, GluonTS, etc.).
• Experience working directly with clients and stakeholders to understand business requirements and deliver ML solutions.
• Strong leadership and team management skills, with the ability to mentor and guide junior team members.
• Excellent communication and presentation skills for both technical and business audiences.

Preferred Qualifications

• Experience with retail, FMCG, or supply chain demand forecasting use cases.
• Exposure to generative AI and LLMs for augmenting forecasting solutions.
• AWS Certification (e.g., AWS Certified Machine Learning – Specialty).

What We Offer

• Opportunity to lead impactful demand forecasting projects with global clients.
• Exposure to cutting-edge ML, AI, and AWS technologies.
• Collaborative, fast-paced, and growth-oriented environment.
• Competitive compensation and benefits.

A Financial Research Analyst is responsible for gathering, analyzing, and interpreting financial data to support investment decisions, business strategies, or financial forecasting. Their primary role is to provide insights and recommendations based on their research to help guide the organization or clients in making informed financial decisions.

Key Responsibilities:

Data Collection & Analysis:

• Gather financial data from various sources (e.g., financial statements, market reports, industry trends, etc.).
• Analyze financial information, including profit and loss statements, balance sheets, and cash flow reports.

Market and Industry Research:

• Research industry trends, economic conditions, and market conditions to identify investment opportunities or risks.
• Track competitor performance and benchmarking.

Financial Modeling and Forecasting:

• Build and maintain financial models to project future performance, such as forecasting revenue and expenses.
• Use quantitative tools to evaluate investment options and potential financial outcomes.

Report Creation:

• Prepare detailed reports summarizing findings, analyses, and recommendations for internal stakeholders or clients.
• Present research findings to management, clients, or investors in a clear and concise manner.

Investment Recommendations:

• Provide recommendations for investment opportunities, such as stocks, bonds, or alternative investments.
• Assist with the evaluation of portfolios and asset management strategies.

Risk Assessment:

• Assess financial risks related to investments, projects, or business decisions.
• Recommend risk management strategies based on data analysis.

Collaboration & Communication:

• Work closely with other teams, such as investment managers, accountants, or business strategists, to align research with broader business objectives.
• Communicate findings and insights clearly to both financial and non-financial stakeholders.

RESPONSIBILITIES:

• Design, build, execute financial, strategic, and operational analysis across the company and products
• Visa arrangement
• Assist in quarterly and annual budgeting, planning, and forecasting process 
• Assist in month-end finance process including closing books, audit, Invoicing, A/R report, etc
• Assist in managing the HRIS system including data updates of all employee information changes and additions; ensure integrity and accuracy of People data 
• Monitor and report on all key HR metrics; manage the design, implementation and tracking of all People team KPIs 
• Provide useful data to help guide decision-making, and allow the company to scale effectively and efficiently
• Identify and recommend methods to automate, simplify, and enhance processes, procedures, and technology to support the finance and operations team

REQUIREMENTS:

• Must have completed Chartered Accountancy (CA) course
• 1-3 years of experience in finance and operations, preferably in a high-growth tech environment 
• Must show documented proficiency in project management - from project design to evaluation 
• Attention to detail; experience with analytics, metrics and business consulting skills preferred
• Candidate must be able to effectively synthesize disparate quantitative and qualitative data sets to make data-driven decisions quickly for the organization
• Ability to diagnose problems with strategic thinking skills, as well as drive appropriate solutions with self-initiative preferred
• Strong communication and collaborative skills to effectively support and connect with a diverse team
• Obsessive around moving critical business metrics and products