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• Partners with business stakeholders to translate business objectives into clearly defined analytical projects.
• Identify opportunities for text analytics and NLP to enhance the core product platform, select the best machine learning techniques for the specific business problem and then build the models that solve the problem.
• Own the end-end process, from recognizing the problem to implementing the solution.
• Define the variables and their inter-relationships and extract the data from our data repositories, leveraging infrastructure including Cloud computing solutions and relational database environments.
• Build predictive models that are accurate and robust and that help our customers to utilize the core platform to the maximum extent.

• 12 to 15 yrs of experience.
• An advanced degree in predictive analytics, machine learning, artificial intelligence; or a degree in programming and significant experience with text analytics/NLP. He shall have a strong background in machine learning (unsupervised and supervised techniques). In particular, excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, logistic regression, MLPs, RNNs, etc.
• Experience with text mining, parsing, and classification using state-of-the-art techniques.
• Experience with information retrieval, Natural Language Processing, Natural Language
• Understanding and Neural Language Modeling.
• Ability to evaluate the quality of ML models and to define the right performance metrics for models in accordance with the requirements of the core platform.
• Experience in the Python data science ecosystem: Pandas, NumPy, SciPy, sci-kit-learn, NLTK, Gensim, etc.
• Excellent verbal and written communication skills, particularly possessing the ability to share technical results and recommendations to both technical and non-technical audiences.
• Ability to perform high-level work both independently and collaboratively as a project member or leader on multiple projects.

Greetings , Wissen Technology is Hiring for the position of Data Engineer

Please find the Job Description for your Reference:

JD

• Design, develop, and maintain data pipelines on AWS EMR (Elastic MapReduce) to support data processing and analytics.
• Implement data ingestion processes from various sources including APIs, databases, and flat files.
• Optimize and tune big data workflows for performance and scalability.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
• Manage and monitor EMR clusters, ensuring high availability and reliability.
• Develop ETL (Extract, Transform, Load) processes to cleanse, transform, and store data in data lakes and data warehouses.
• Implement data security best practices to ensure data is protected and compliant with relevant regulations.
• Create and maintain technical documentation related to data pipelines, workflows, and infrastructure.
• Troubleshoot and resolve issues related to data processing and EMR cluster performance.

Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 5+ years of experience in data engineering, with a focus on big data technologies.
• Strong experience with AWS services, particularly EMR, S3, Redshift, Lambda, and Glue.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with big data frameworks and tools such as Hadoop, Spark, Hive, and Pig.
• Solid understanding of data modeling, ETL processes, and data warehousing concepts.
• Experience with SQL and NoSQL databases.
• Familiarity with CI/CD pipelines and version control systems (e.g., Git).
• Strong problem-solving skills and the ability to work independently and collaboratively in a team environment

Data driven decision-making is core to advertising technology at AdElement. We are looking for sharp, disciplined, and highly quantitative machine learning/ artificial intellignce engineers with big data experience and a passion for digital marketing to help drive informed decision-making. You will work with top-talent and cutting edge technology and have a unique opportunity to turn your insights into products influencing billions. The potential candidate will have an extensive background in distributed training frameworks, will have experience to deploy related machine learning models end to end, and will have some experience in data-driven decision making of machine learning infrastructure enhancement. This is your chance to leave your legacy and be part of a highly successful and growing company.

Required Skills

- 3+ years of industry experience with Java/ Python in a programming intensive role

- 3+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, graph mining, deep learning

- 3+ years of industry experience with distributed computing frameworks such as Hadoop/Spark, Kubernetes ecosystem, etc

- 3+ years of industry experience with popular deep learning frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, etc

- 3+ years of industry experience with major cloud computing services

- An effective communicator with the ability to explain technical concepts to a non-technical audience

- (Preferred) Prior experience with ads product development (e.g., DSP/ad-exchange/SSP)

- Able to lead a small team of AI/ML Engineers to achieve business objectives

Responsibilities

- Collaborate across multiple teams - Data Science, Operations & Engineering on unique machine learning system challenges at scale

- Leverage distributed training systems to build scalable machine learning pipelines including ETL, model training and deployments in Real-Time Bidding space. 

- Design and implement solutions to optimize distributed training execution in terms of model hyperparameter optimization, model training/inference latency and system-level bottlenecks  

- Research state-of-the-art machine learning infrastructures to improve data healthiness, model quality and state management during the lifecycle of ML models refresh.

- Optimize integration between popular machine learning libraries and cloud ML and data processing frameworks. 

- Build Deep Learning models and algorithms with optimal parallelism and performance on CPUs/ GPUs.

- Work with top management on defining teams goals and objectives.

Education

- MTech or Ph.D. in Computer Science, Software Engineering, Mathematics or related fields

• Develop, train, and optimize machine learning models using Python, ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and other relevant technologies.
• Implement MLOps best practices, including model deployment, monitoring, and versioning.
• Utilize Vertex AI, MLFlow, KubeFlow, TFX, and other relevant MLOps tools and frameworks to streamline the machine learning lifecycle.
• Collaborate with cross-functional teams to design and implement CI/CD pipelines for continuous integration and deployment using tools such as GitHub Actions, TeamCity, and similar platforms.
• Conduct research and stay up-to-date with the latest advancements in machine learning, deep learning, and MLOps technologies.
• Provide guidance and support to data scientists and software engineers on best practices for machine learning development and deployment.
• Assist in developing tooling strategies by evaluating various options, vendors, and product roadmaps to enhance the efficiency and effectiveness of our AI and data science initiatives.

Responsibilities:

• Identify relevant data sources - a combination of data sources to make it useful.
• Build the automation of the collection processes.
• Pre-processing of structured and unstructured data.
• Handle large amounts of information to create the input to analytical Models.
• Build predictive models and machine-learning algorithms Innovate Machine-Learning , Deep-Learning algorithms.
• Build Network graphs , NLP , Forecasting Models Building data pipelines for end-to-end solutions.
• Propose solutions and strategies to business challenges. Collaborate with product development teams and communicate with the Senior Leadership teams.
• Participate in Problem solving sessions

Requirements:

• Bachelor's degree in a highly quantitative field (e.g. Computer Science , Engineering , Physics , Math , Operations Research , etc) or equivalent experience.
• Extensive machine learning and algorithmic background with a deep level understanding of at least one of the following areas: supervised and unsupervised learning methods , reinforcement learning , deep learning , Bayesian inference , Network graphs , Natural Language Processing Analytical mind and business acumen
• Strong math skills (e.g. statistics , algebra)
• Problem-solving aptitude Excellent communication skills with ability to communicate technical information.
• Fluency with at least one data science/analytics programming language (e.g. Python , R , Julia).
• Start-up experience is a plus Ideally 5-8 years of advanced analytics experience in startups/marquee com

Required Skills:

Machine Learning, Deep Learning, Algorithms, Computer Science, Engineering, Operations Research, Math Skills, Communication Skills, SAAS Product, IT Services, Artificial Intelligence, ERP, Product Management, Automation, Analytical Models, Predictive Models, NLP, Forecasting Models, Product Development, Leadership, Problem Solving, Unsupervised Learning, Reinforcement Learning, Natural Language Processing, Algebra, Data Science, Programming Language, Python, Julia

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:

• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

Position Name: Software Developer

Required Experience: 3+ Years

Number of positions: 4

Qualifications: Master’s or Bachelor s degree in Engineering, Computer Science, or equivalent (BE/BTech or MS in Computer Science).

Key Skills: Python, Django, Ngnix, Linux, Sanic, Pandas, Numpy, Snowflake, SciPy, Data Visualization, RedShift, BigData, Charting

Compensation - As per industry standards.

Joining - Immediate joining is preferrable.

Required Skills:

• Strong Experience in Python and web frameworks like Django, Tornado and/or Flask
• Experience in data analytics using standard python libraries using Pandas, NumPy, MatPlotLib
• Conversant in implementing charts using charting libraries like Highcharts, d3.js, c3.js, dc.js and data Visualization tools like Plotly, GGPlot
• Handling and using large databases and Datawarehouse technologies like MongoDB, MySQL, BigData, Snowflake, Redshift.
• Experience in building APIs, Multi-threading for tasks on Linux platform
• Exposure to finance and capital markets will be added advantage. 
• Strong understanding of software design principles, algorithms, data structures, design patterns, and multithreading concepts.
• Worked on building highly-available distributed systems on cloud infrastructure or have had exposure to architectural pattern of a large, high-scale web application.
• Strong understanding of software design principles, algorithms, data structures, design patterns, and multithreading concepts.
• Basic understanding of front-end technologies, such as JavaScript, HTML5, and CSS3

Company Description:

Reval Analytical Services is a fully-owned subsidiary of Virtua Research Inc. US. It is a financial services technology company focused on consensus analytics, peer analytics and Web-enabled information delivery. The Company’s unique combination of investment research experience, modeling expertise, and software development capabilities enables it to provide industry-leading financial research tools and services for investors, analysts, and corporate management.

Website: http://www.virtuaresearch.com" target="_blank">www.virtuaresearch.com