Analyst jobs Gurgaon

Job Requirements
Education Bachelor's degree in business or related field is preferred
Relevant Experience * 2 years+ of experience in inventory demand planning * Proven track record in setting and achieving inventory short, medium and long-range inventory plans * Exceptional ability to communicate complex analytics in a clear, actionable manner to influence decision-making * Strong interpersonal skills to effectively collaborate with internal teams and external parties * Skilled in monitoring and measuring inventory demand planning performance against goals, with the ability to provide insights and make timely adjustments * Results-driven mindset with the ability to balance strategic planning and tactical execution Behavioural Skills * Delivery Excellence * Business Disposition * Social Intelligence * Innovation & Agility * Purposeful Leadership Technical Skills * Strong analytical skills with proficiency in inventory management software and tools (e.g., PDI, Relex) * Advanced proficiency in Excel and other data analysis tools; experience with visualization tools e.g., Power BI, Tableau etc. Knowledge * Data Analytics * Good knowledge in Power BI, MS Excel and Tableau

As a Quality Assurance Analyst at Bupa Technology, you will drive the quality engineering strategy across crews/program level, ensuring the delivery of Bupa releases on time.

As a Senior Quality Assurance Analyst at Bupa Technology, you will play a pivotal role in leading quality assurance initiatives across multiple teams and programs, ensuring timely and successful delivery of Bupa releases.

You will have a key role in advancing how GIA utilises available data for its risk assessment and assurance planning, aiming to integrate this into a real-time data-led ecosystem. Your responsibilities include driving innovation and increasing the productivity of the audit function through the use of data, developing predictive models and use of Data Science techniques in the department.

The Senior Demand Planner Analyst must demonstrate the ability to effectively lead their respective staff in properly plan for shifts in consumer purchasing, while optimizing product inventory levels. Product forecasting will be managed in Relex (inventory planning system), interfacing with Merchants and Vendors for their assigned area of business, ensuring proper planning for item introductions, promotions, item discontinuation, and more.

Opportunity to lead FP&A and financial reporting for a global investment operations team, driving strategic planning, forecasting, and performance analysis. Ideal for professionals with 5-7 years of consulting finance experience and strong data visualization and modeling skills.

Position:

ML EngineerJob type:

Techno-FunctionalPreferred education qualifications:

Bachelor/ Master's degree in computer science, Data Science, Machine Learning OR related technical degreeJob location:

IndiaGeography:

SAPMENARequired experience:

6-8 YearsPreferred profile/ skills:

• 5+ years in developing and deploying enterprise-scale ML solutions
• [Mandatory] Proven track record in data analysis (EDA, profiling, sampling), data engineering (wrangling, storage, pipelines, orchestration),
• [Mandatory] Proficiency in Data Science/ML algorithms such as regression, classification, clustering, decision trees, random forest, gradient boosting, recommendation, dimensionality reduction
• [Mandatory] Experience in ML algorithms such as ARIMA, Prophet, Random Forests, and Gradient Boosting algorithms (XGBoost, LightGBM, CatBoost)
• [Mandatory] Prior experience on MLOps with Kubeflow or TFX
• [Mandatory] Experience in model explainability with Shapley plot and data drift detection metrics.
• [Mandatory] Advanced programming skills with Python and SQL
• [Mandatory] Prior experience on building scalable ML pipelines & deploying ML models on Google Cloud
• [Mandatory] Proven expertise in ML pipeline optimization and monitoring the model's performance over time
• [Mandatory] Proficiency in version control systems such as GitHub
• Experience with feature engineering optimization and ML model fine tuning is preferred
• Google Cloud Machine Learning certifications will be a big plus
• Experience in Beauty or Retail/FMCG industry is preferred
• Experience in training with large volume of data (>100 GB)
• Experience in delivering AI-ML projects using Agile methodologies is preferred
• Proven ability to effectively communicate technical concepts and results to technical & business audiences in a comprehensive manner
• Proven ability to work proactively and independently to address product requirements and design optimal solutions
• Fluency in English, strong communication and organizational capabilities; and ability to work in a matrix/ multidisciplinary team

Job objectives:

Design, develop, deploy, and maintain data science and machine learning solutions to meet enterprise goals. Collaborate with product managers, data scientists & analysts to identify innovative & optimal machine learning solutions that leverage data to meet business goals. Contribute to development, rollout and onboarding of data scientists and ML use-cases to enterprise wide MLOps framework. Scale the proven ML use-cases across the SAPMENA region. Be responsible for optimal ML costs.Job description:

• Deep understanding of business/functional needs, problem statements and objectives/success criteria
• Collaborate with internal and external stakeholders including business, data scientists, project and partners teams in translating business and functional needs into ML problem statements and specific deliverables
• Develop best-fit end-to-end ML solutions including but not limited to algorithms, models, pipelines, training, inference, testing, performance tuning, deployments
• Review MVP implementations, provide recommendations and ensure ML best practices and guidelines are followed
• Act as 'Owner' of end-to-end machine learning systems and their scaling
• Translate machine learning algorithms into production-level code with distributed training, custom containers and optimal model serving
• Industrialize end-to-end MLOps life cycle management activities including model registry, pipelines, experiments, feature store, CI-CD-CT-CE with Kubeflow/TFX
• Accountable for creating, monitoring drifts leveraging continuous evaluation tools and optimizing performance and overall costs
• Evaluate, establish guidelines, and lead transformation with emerging technologies and practices for Data Science, ML, MLOps, Data Ops

 Collaborate with solution architect, data engineers, business stakeholders, business analysts, and DQ testers to ensure data management and data governance framework is defined as critical components.
 Design and develop data models using industry-standard modeling techniques and tools.