Inside Sales Executive- website selling campaign

Roles & Responsibility

• Developing Hybrid Mobile Apps using IONIC 5 or 6 + ANGULAR + Typescript & CAPACITOR
• Independently compile and deploy apps - both on Android & Apple platforms
• With Plugins such as Google Maps, Payment Gateways, Push Notifications, QR Codes, WiFi, NFC, etc is good to have
• Optimize for multi-device iPhone, iPad, Tablet & Smartphones
• Experience in HTML5, CSS3, & JavaScript
• Good understanding of REST APIs & JSON
• Ensuring high performance on mobile and desktop
• Work on bug fixing and improving application performance

Desired skills

Knowledge of all aspects of Angular framework:Components, Directives, Lazy Loading, Angular lifecycle hooks, service, moduleRxJSWebpackAngular Router usageJSON/XML parsing Angular CLI Command line usage of toolsHTML5, CSS3 with responsive web development and related web technologiesCSS precompilers like SCSS and LESSNeed to know usage of third party libraries like Angular Material, node-sass etc.Knowledge of PWA, UI adaptability using media queries via SCSS specificationIntegration of payment gateways, wallets, analytics and browser notifications

5+ years of experience designing, developing, validating, and automating ETL processes 3+ years of experience traditional ETL tools such as Visual Studio, SQL Server Management Studio, SSIS, SSAS and SSRS 2+ years of experience with cloud technologies and platforms, such as: Kubernetes, Spark, Kafka, Azure Data Factory, Snowflake, ML Flow, Databricks, Airflow or similar Must have experience with designing and implementing data access layers Must be an expert with SQL/T-SQL and Python Must have experience in Kafka Define and implement data models with various database technologies like MongoDB, CosmosDB, Neo4j, MariaDB and SQL Serve Ingest and publish data from sources and to destinations via an API Exposure to ETL/ELT with using Kafka or Azure Event Hubs with Spark or Databricks is a plus Exposure to healthcare technologies and integrations for FHIR API, HL7 or other HIE protocols is a plus

Skills Required :

Designing, Developing, ETL, Visual Studio, Python, Spark, Kubernetes, Kafka, Azure Data Factory, SQL Server, Airflow, Databricks, T-SQL, MongoDB, CosmosDB, Snowflake, SSIS, SSAS, SSRS, FHIR API, HL7, HIE Protocols

• Analyze complex data sets to identify trends, patterns, and insights to drive business decisions.

• Collaborate with cross-functional teams in an Agile environment to define and implement data-driven solutions.

• Create and maintain detailed reports and dashboards to track key performance indicators (KPIs).

• Work closely with product owners, developers, and stakeholders to ensure data requirements are met effectively.

• Utilize Jira for task management, sprint planning, and tracking project progress.

• Provide guidance and mentorship to junior team members in data analysis techniques and best practices.

Responsibilities:

• Lead simultaneous development for multiple business verticals.
• Design & develop highly scalable, reliable, secure, and fault-tolerant systems.
• Ensure that exceptional standards are maintained in all aspects of engineering.
• Collaborate with other engineering teams to learn and share best practices.
• Take ownership of technical performance metrics and strive actively to improve them.
• Mentors junior members of the team and contributes to code reviews.

Requirements:

• A passion to solve tough engineering/data challenges.
• Be well versed with cloud computing platforms AWS/GCP
• Experience with SQL technologies (MySQL, PostgreSQL)
• Experience working with NoSQL technologies (MongoDB, ElasticSearch)
• Excellent Programming skills in Python/Java/GoLang
• Big Data streaming services (Kinesis, Kafka, RabbitMQ)
• Distributed cache systems(Redis, Memcache)
• Advanced data solutions(BigQuery, RedShift, DynamoDB, Cassandra)
• Automated testing frameworks and CI/CD pipelines Infrastructure orchestration(Docker/Kubernetes/Nginx)
• Cloud-native tech like Lambda, ASG, CDN, ELB, SNS/SQS, S3 Route53 SES

Responsibilities

• Manage and drive a team of Data Analysts and Sr. Data Analysts to provide logistics and supply chain solutions.
• Conduct meetings with Clients to gather the requirements and understand the scope.
• Conduct meetings with internal stake holders to walk them through the solution and handover the analysis.
• Define business problems, identify solutions, provide analysis and insights from the client's data.
• 5 Conduct scheduled progress reviews on all projects and interact with onsite team daily.
• Ensure solutions are delivered error free and submitted on time.
• Implement ETL processes using Pentaho Data Integration (Pentaho ETL)Design and implement data models in Hadoop.
• Provide end-user training and technical assistance to maximize utilization of tools.
• Deliver technical guidance to team, including hands-on development as necessary; oversee standards, change controls and documentation library for training and reuse.

Requirements

• Bachelor's degree in Engineering.
• 16+ years of experience in Supply Chain and logistics or related industry and Analytics experience.
• 3 years of experience in team handling(8+People) and interacting with the executive leadership teams.
• Strong project and time management skills with ability to multitask and prioritize workload.
• Solid expertise with MS Excel, SQL, any visualization tools like Tableau/Power BI, any ETL tools.
• Proficiency in Hadoop / Hive.
• Experience Pentaho ETL, Pentaho Visualization API, Tableau.
• Hands on experience of working with Big data sets (Data sets with millions of records).
• Strong technical and Management experience.

Desired Skills and Experience

• NET,ASP.NET

Job Description: 

Machine Learning / AI Engineer (with 3+ years of experience)

We are seeking a highly skilled and passionate Machine Learning / AI Engineer to join our newly established data science practice area. In this role, you will primarily focus on working with Large Language Models (LLMs) and contribute to building generative AI applications. This position offers an exciting opportunity to shape the future of AI technology while charting an interesting career path within our organization.

Responsibilities:

1. Develop and implement machine learning models: Utilize your expertise in machine learning and artificial intelligence to design, develop, and deploy cutting-edge models, with a particular emphasis on Large Language Models (LLMs). Apply your knowledge to solve complex problems and optimize performance.

2. Building generative AI applications: Collaborate with cross-functional teams to conceptualize, design, and build innovative generative AI applications. Work on projects that push the boundaries of AI technology and deliver impactful solutions to real-world problems.

3. Data preprocessing and analysis: Collect, clean, and preprocess large volumes of data for training and evaluation purposes. Conduct exploratory data analysis to gain insights and identify patterns that can enhance the performance of AI models.

4. Model training and evaluation: Develop robust training pipelines for machine learning models, incorporating best practices in model selection, feature engineering, and hyperparameter tuning. Evaluate model performance using appropriate metrics and iterate on the models to improve accuracy and efficiency.

5. Research and stay up to date: Keep abreast of the latest advancements in machine learning, natural language processing, and generative AI. Stay informed about industry trends, emerging techniques, and open-source libraries, and apply relevant findings to enhance the team's capabilities.

6. Collaborate and communicate effectively: Work closely with a multidisciplinary team of data scientists, software engineers, and domain experts to drive AI initiatives. Clearly communicate complex technical concepts and findings to both technical and non-technical stakeholders.

7. Experimentation and prototyping: Explore novel ideas, experiment with new algorithms, and prototype innovative solutions. Foster a culture of innovation and contribute to the continuous improvement of AI methodologies and practices within the organization.

Requirements:

1. Education: Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Relevant certifications in machine learning, deep learning, or AI are a plus.

2. Experience: A minimum of 3+ years of professional experience as a Machine Learning / AI Engineer, with a proven track record of developing and deploying machine learning models in real-world applications.

3. Strong programming skills: Proficiency in Python and experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, pandas). Experience with cloud platforms (e.g., AWS, Azure, GCP) for model deployment is preferred.

4. Deep-learning expertise: Strong understanding of deep learning architectures (e.g., convolutional neural networks, recurrent neural networks, transformers) and familiarity with Large Language Models (LLMs) such as GPT-3, GPT-4, or equivalent.

5. Natural Language Processing (NLP) knowledge: Familiarity with NLP techniques, including tokenization, word embeddings, named entity recognition, sentiment analysis, text classification, and language generation.

6. Data manipulation and preprocessing skills: Proficiency in data manipulation using SQL and experience with data preprocessing techniques (e.g., cleaning, normalization, feature engineering). Familiarity with big data tools (e.g., Spark) is a plus.

7. Problem-solving and analytical thinking: Strong analytical and problem-solving abilities, with a keen eye for detail. Demonstrated experience in translating complex business requirements into practical machine learning solutions.

8. Communication and collaboration: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to diverse stakeholders