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JOB SUMMARY: The Senior Associate supports the Data Analytics Manager by proposing relevant analytics procedures/tools, executing the analytics and also developing visualization outputs for audits, continuous monitoring/auditing and IA initiatives. The individual’s responsibilities include -
Understanding audit and/or project objectives and assisting the manager in preparing the plan and timelines.
Working with the Process/BU/IA teams for gathering requirements for continuous monitoring/auditing projects.
Working with Internal audit project teams to understand the analytics requirements for audit engagements.
Independently build pilot/prototype, determine appropriate visual tool and design the views to meet project objectives.
Proficient in data management and data mining.
Highly skilled on visualization tools like Qlik View, Qlik Sense, Power BI, Tableau, Alteryx etc.
Working with Data Analytics Manager to develop analytics program aligned to the overall audit plan.
Showcasing analytics capability to Process management teams to increase adoption of continuous monitoring.
Establishing and maintaining relationships with all key stakeholders of internal audit.
Coaching other data analysts on analytics procedures, coding and tools.
Taking a significant and active role in developing and driving Internal Audit Data Analytics quality and knowledge sharing to enhance the value provided to Internal Audit stakeholders.
Ensuring timely and accurate time tracking.
Continuously focusing on self-development by attending trainings, seminars and acquiring relevant certifications.
SKILLS:
Mandatory Skills:
- Advanced Understanding of Adobe Analytics as an Architect or at the least Business Practitioner.
- Possess excellent analytical skills to understand the intricacies of the data and visualization.
- Advanced MS Excel skills.
- Good communication skills.
- Team Building & Handling
Desired Skills:
- Hands-on Visualization Tools like Tableau and Power BI.
- Must have understanding on Adobe DTM and Launch (Tag Management Systems).
- SQL – Basic.
What you’ll be responsible for:
- Monitor the site performance on a daily basis.
- Understand user behaviour and create actionable dashboards.
- Create and maintain daily/weekly/monthly reports.
- Analyse and Audit data to generate dashboards.
- Measure and report performance of marketing campaigns, gain insight and assess against goals.
- Hands-on knowledge with user behaviour tracking systems and methodologies.
- Identifying key needs or gaps and provide leadership to close those gaps.
Challenges (also responsible) you’ll be facing in the role:
- Understand client requirement and create ad hoc reports/Recommendations.
- Provide meaningful insights from data to make operational and strategic decisions for clients.
- Strong Understanding of various technologies being used in the digital transformation space.
- Should possess Data Visualization skills to help build interactive reports.
- Independent and proactive self-starter.
Requirements
Senior Software Engineer
MUST HAVE:
POWER BI with PLSQL
experience: 5+ YEARS
cost: 18 LPA
WHF- HYBRID
Work Location : Chennai
Experience Level : 5+yrs
Package : Upto 18 LPA
Notice Period : Immediate Joiners
It's a full-time opportunity with our client.
Mandatory Skills:Machine Learning,Python,Tableau & SQL
Job Requirements:
--2+ years of industry experience in predictive modeling, data science, and Analysis.
--Experience with ML models including but not limited to Regression, Random Forests, XGBoost.
--Experience in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models.
--Experience writing code in Python and SQL with documentation for reproducibility.
--Strong Proficiency in Tableau.
--Experience handling big datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL.
--Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations.
--AWS Sagemaker experience is a plus not required.
- Building and operationalizing large scale enterprise data solutions and applications using one or more of AZURE data and analytics services in combination with custom solutions - Azure Synapse/Azure SQL DWH, Azure Data Lake, Azure Blob Storage, Spark, HDInsights, Databricks, CosmosDB, EventHub/IOTHub.
- Experience in migrating on-premise data warehouses to data platforms on AZURE cloud.
- Designing and implementing data engineering, ingestion, and transformation functions
- Experience with Azure Analysis Services
- Experience in Power BI
- Experience with third-party solutions like Attunity/Stream sets, Informatica
- Experience with PreSales activities (Responding to RFPs, Executing Quick POCs)
- Capacity Planning and Performance Tuning on Azure Stack and Spark.
We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.
Skills:
- 5+ years deploying Machine Learning pipelines in large enterprise production systems.
- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.
Roles and Responsibilities:
Deploying ML models into production, and scaling them to serve millions of customers.
Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.
Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.
Provide software design and programming support to projects.
Qualifications & Experience:
Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.