Retail jobs within Technology & Telecoms

This role involves building and scaling a strategic Go-To-Market service to help regional FMCG brands grow beyond their core markets using a combination of digital marketing, retail activation, and data-driven insights. The Vice President will own the full P&L, lead cross-functional teams, and work closely with founders to drive innovation, execution, and long-term growth.

The role of Category Manager involves managing and driving the growth of retail categories within the technology and telecoms industry. You will work closely with cross-functional teams to implement strategies that maximise sales and enhance customer experience in Bengaluru.

Role Summary The Zone Network and Security Project Manager will be responsible for the co-ordination of designing, implementing, and maintaining secure IT infrastructure solutions. The role's main responsibility is to ensure the organization's IT systems remain resilient, compliant, and aligned with business objectives. The ideal candidate will have a strong technical background in network engineering and cybersecurity coupled with hands-on experience in project management and cross-functional collaboration. Experience with retail and cloud infrastructure a plus.Key Responsibilities

Project Management

• Lead network and system migration projects.
• Collaborate with suppliers and stakeholders, including Retail IT, to design and test IT infrastructure solutions.
• Ensure timely delivery and successful execution of IT and security projects.

Network Engineering and Security

• Advise and co-ordinate the design, configuration, and management of company network security infrastructure (e.g., Meraki, Fortinet, Zscaler).
• Lead the implementation and maintenance of secure WAN solutions (ADSL, MPLS, SD-WAN).
• Develop and enforce security compliance measures, including IPSec VPN management.
• Support global connectivity solutions, such as Meraki, Cloudi-fi, and Zscaler.
• Design, implement, and manage Zscaler Private Access (ZPA) solutions for secure remote access to internal applications across our 3500 retail stores in the Zone.
• Configure and optimize Zscaler Secure Internet Access (ZIA) policies for web security, threat prevention, and data loss prevention for our 3500 retail stores in the Zone.
• Troubleshoot and resolve issues related to Zscaler ZPA and ZIA deployments, ensuring optimal performance and security.

Cloud Infrastructure and Automation

• Working knowledge of cloud-based systems in Azure and AliCloud, including AAD server migrations.

Cybersecurity and Compliance

• Implement and support data loss prevention (DLP) tools such as CrowdStrike.
• Lead cybersecurity IT training where needed.

IT Systems Administration

• Monitor and maintain system performance using tools like ThousandEyes.
• Strong analytical skills and high proficiency in using PowerBI and Excel.

Collaboration and Support

• Manage access controls using SharePoint.
• Provide project workflow customization and ServiceNOW and Confluence knowledge base access management.
• Support cross-functional teams with IT tools, meeting room setups, and collaboration platforms (Teams, SharePoint, ServiceNOW, Confluence).

Qualifications and Skills

Technical Certifications (bonus but not required)

• CCNP (Cisco Certified Network Professional).
• PMP (Project Management Professional).
• Zscaler Certifications (e.g., Zscaler Certified Administrator, Zscaler Certified Professional) are a significant plus.

Technical Expertise

• Proficient in network technologies: Cisco Meraki, Palo Alto Firewalls.
• Strong skills in cloud technologies: Azure, AliCloud.
• Advanced knowledge of cybersecurity tools: CrowdStrike, CyberArk.
• Extensive hands-on experience with Zscaler, specifically Zscaler Private Access (ZPA) and Zscaler Secure Internet Access (ZIA) modules.

Preferred Experience

• 5+ years of experience in network engineering and cybersecurity roles.
• Proven track record in IT infrastructure management and cloud migration projects.

Demonstrated experience in deploying, configuring, and maintaining Zscaler Private Access (ZPA) and Zscaler Secure Internet Access (ZIA) in an enterprise environment, particularly within a large-scale retail contextLocation- Hyderabad

Mode- Hybrid, 3 Days WFO

Data Scientist (IT)Position:

Data ScientistJob type:

Techno-FunctionalPreferred education qualifications:

Bachelor/ Master's degree in Statistics, Operation Research, Computer Science, Data Science OR related quantitative fieldJob location:

IndiaGeography:

SAPMENARequired experience:

6-8 YearsPreferred profile/ skills:



§ 5+ years in developing and implementing forecasting models

§ [Mandatory] Proven track record in data analysis (EDA, profiling, sampling), data engineering (wrangling, storage, pipelines, orchestration)

§ [Mandatory] Proven expertise in time series analysis, regression analysis, and other statistical modelling techniques

§ [Mandatory] Experience in ML algorithms such as ARIMA, Prophet, Random Forests, and Gradient Boosting algorithms (XGBoost, LightGBM, CatBoost)

§ [Mandatory] Experience in model explainability with Shapley plot and data drift detection metrics.

§ [Mandatory] Strong programming & analysis skills with Python and SQL, including experience with relevant forecasting packages

§ [Mandatory] Prior experience on Data Science & ML Engineering on Google Cloud

§ [Mandatory] Proficiency in version control systems such as GitHub

§ [Mandatory] Strong organizational capabilities; and ability to work in a matrix/ multidisciplinary team

§ [Mandatory] Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical audience

§ Experience in Beauty or Retail/FMCG industry is preferred

§ Experience in handling large volume of data (>100 GB)

§ Experience in delivering AI-ML projects using Agile methodologies is preferred

§ Proven ability to work proactively and independently to address product requirements and design optimal solutionsJob objectives:

Design, develop, implement, and maintain data science and machine learning solutions to meet enterprise goals. Collaborate with cross-functional teams to leverage statistical modeling, machine learning, and data mining techniques to improve forecast accuracy and aid strategic decision-making across the organization. Scale the proven AI-ML Product across the SAPMENA region.Job description:§ Deep understanding of business/functional needs, problem statements and objectives/success criteria

§ Develop and maintain sophisticated statistical forecasting models, incorporating factors such as seasonality, promotions, media, traffic and other economic indicators

§ Collaborate with internal and external stakeholders including business, data scientists & product team to understand the business and product needs and translate them into actionable data-driven solutions

§ Review MVP implementations, provide recommendations and ensure Data Science best practices and guidelines are followed

§ Evaluate and compare the performance of different forecasting models, recommending optimal approaches for various business scenarios

§ Analyze large and complex datasets to identify patterns, insights, and potential risks and opportunities

§ Communicate forecasting results and insights to both technical and non-technical audiences through clear visualizations and presentations

§ Stay up to date with the latest advancements in forecasting techniques and technologies, continuously seeking opportunities for improvement

§ Contribute to the development of a robust data infrastructure for AI-ML solutions, ensuring data quality and accessibility

§ Collaborate with other data scientists and engineers to build and deploy scalable AI-ML solutions

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

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