Manager jobs in India

Qualifications & Required Skills: Full-Time

bachelor's or master's degree in engineering/technology, computer science, information technology, or related fields.

 10+ years of total experience in data modeling and database design and experience in Retail domain will be added advantage.

 8+ years of experience in data engineering development and support.

 3+ years of experience in leading technical team of data engineers and BI engineers  Proficiency in data modeling tools such as Erwin, ER/Studio, or similar tools.

 Strong knowledge of Azure cloud infrastructure and development using SQL/Python/PySpark using ADF, Synapse and Databricks.

 Hands-on experience with Azure Data Factory, Azure Synapse Analytics, Azure Analysis Services, Azure Databricks, Blob Storage, Python/PySpark, Logic Apps, Key Vault, and Azure functions.

 Strong communication, interpersonal, collaboration skills along with leadership capabilities.

 Ability to work effectively in a fast-paced, dynamic environment as cloud SME.

 Act as single point of contact for all kinds of data management related queries to make data decisions.

 Design and manage centralized, end-to-end data architecture solutions, such as- Data model designs, Database development standards, Implementation and management of data warehouses, Data analytics systems.

 Conduct continuous audits of data management system performance and refine where necessary.

 Identify bottlenecks, optimize queries, and implement caching mechanisms to enhance data processing speed.

 Work to integrate disparate data sources, including internal databases and external application programming interfaces (APIs), enabling organizations to derive insights from a holistic view of the data.

 Ensure data privacy measures comply with regulatory standards.Preferred

* Azure Data Factory (ADF), Databricks certification is a plus.

* Data Architect or Azure cloud Solution Architect certification is a plus.Technologies we use: Azure Data Factory, Databricks, Azure Synapse, Azure Tabular, Azure Functions, Logic Apps, Key Vault, DevOps, Python, PySpark, Scripting (PowerShell, Bash), Git, Terraform, Power BI, Snowflake

• The Quality Engineers works with Architects, Solution Designers, Developers, Product Owners, Project Managers and others to help ensure high quality and timely delivery
• The Quality Engineers plans and executes manual/automated/Non-Functional testing throughout the development cycle throughout the project, and communicates frequently with team members regarding quality status, and helps to resolve test impacts

To perform analysis of programme, plan the creation and execution of testing strategies and testing tasks whilst conforming to UK IT Testing Services processes and standards.
To work with the Test Manager, QA Software Test Engineers, IT Change Specialists and other key stakeholders to ensure integration, system, end to end and regression testing is performed as specified and intended by the Business stories and Functional Requirements documentation.

To perform analysis of programme, plan the creation and execution of testing strategies and testing tasks iwhilst conforming to UK IT Testing Services processes and standards.
To work with the Test Manager, QA Software Test Engineers, IT Change Specialists and other key stakeholders to ensure integration, system, end to end and regression testing is performed as specified and intended by the Business stories and Functional Requirements documentation.

To perform analysis of programme, plan the creation and execution of testing strategies and testing tasks whilst conforming to UK IT Testing Services processes and standards.

To work with the Test Manager, QA Software Test Engineers, IT Change Specialists and other key stakeholders to ensure integration, system, end to end and regression testing is performed as specified and intended by the Business stories and Functional Requirements documentation.

Job Requirements Education

* Bachelor's degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)

* Master's degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.) Relevant Experience

*3 - 4 years for Data Scientist

* Relevant working experience in a data science/advanced analytics role Behavioural Skills

*Delivery Excellence

*Business disposition

*Social intelligence

*Innovation and agility Knowledge

* Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.)

*Statistical modelling using Analytical tools (R, Python, KNIME, etc.)*Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference)

*Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference.

*Practical experience deploying models using MLOps tools and practices (e.g., MLflow, DVC, Docker, etc.)

*Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.)

*Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.)

* Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools

*Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)

* Microsoft Office applications (MS Excel, etc.)

Location- Gurgaon

Job RequirementsEducation

* Bachelor's degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)

* Master's degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.)Relevant Experience

* 5 - 7 years for Data Scientist

* Relevant working experience in a data science/advanced analytics roleBehavioural Skills

* Delivery Excellence

* Business disposition

* Social intelligence

* Innovation and agilityExperience

* Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.)

* Statistical modelling using Analytical tools (R, Python, KNIME, etc.)

* Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference)

* Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference.

* Practical experience deploying models using MLOps tools and practices (e.g., MLflow, DVC, Docker, etc.)

* Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.)

* Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.)

* Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools

* Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)

* Microsoft Office applications (MS Excel, etc.)Roles & Responsibilities

Analytics & Strategy

1. Analyse large-scale structured and unstructured data; develop deep-dive analyses and machine learning models in retail, marketing, merchandising, and other areas of the business

2. Utilize data mining, statistical and machine learning techniques to derive business value from store, product, operations, financial, and customer transactional data

3. Apply multiple algorithms or architectures and recommend the best model with in-depth description to evangelize data-driven business decisions

4. Utilize cloud setup to extract processed data for statistical modelling and big data analysis, and visualization tools to represent large sets of time series/cross-sectional dataOperational Excellence

1. Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project

2. Structure hypothesis, build thoughtful analyses, develop underlying data models and bring clarity to previously undefined problems

3. Partner with Data Engineering to build, design and maintain core data infrastructure, pipelines and data workflows to automate dashboards and analysesStakeholder Engagement

1. Working collaboratively across multiple sets of stakeholders - Business functions, Data Engineers, Data Visualization experts to deliver on project deliverables

2. Articulate complex data science models to business teams and present the insights in easily understandable and innovative formats

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