11+ Supervised learning Jobs in Chennai | Supervised learning Job openings in Chennai

• Research and test novel machine learning approaches for analysing large-scale distributed computing applications.
• Develop production-ready implementations of proposed solutions across different models AI and ML algorithms, including testing on live customer data to improve accuracy,  efficacy, and robustness
• Work closely with other functional teams to integrate implemented systems into the SaaS platform
• Suggest innovative and creative concepts and ideas that would improve the overall platform

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The ideal candidate must have the following qualifications:

• 5 + years experience in practical implementation and deployment of large customer-facing ML based systems.
• MS or M Tech (preferred) in applied mathematics/statistics;  CS or Engineering disciplines are acceptable but must have with strong quantitative and applied mathematical skills
• In-depth working, beyond coursework, familiarity with classical and current ML techniques, both supervised and unsupervised learning techniques and algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimization
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python is a must
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow

Most importantly, you should be someone who is passionate about building new and innovative products that solve tough real-world problems.

Chennai, India

Role Summary

As a Data Engineer, you will be an integral part of our Data Engineering team supporting an event-driven server less data engineering pipeline on AWS cloud, responsible for assisting in the end-to-end analysis, development & maintenance of data pipelines and systems (DataOps). You will work closely with fellow data engineers & production support to ensure the availability and reliability of data for analytics and business intelligence purposes.

Requirements:

·      Around 4 years of working experience in data warehousing / BI system.

·      Strong hands-on experience with Snowflake AND strong programming skills in Python

·      Strong hands-on SQL skills

·      Knowledge with any of the cloud databases such as Snowflake,Redshift,Google BigQuery,RDS,etc.

·      Knowledge on debt for cloud databases

·      AWS Services such as SNS, SQS, ECS, Docker, Kinesis & Lambda functions

·      Solid understanding of ETL processes, and data warehousing concepts

·      Familiarity with version control systems (e.g., Git/bit bucket, etc.) and collaborative development practices in an agile framework

·      Experience with scrum methodologies

·      Infrastructure build tools such as CFT / Terraform is a plus.

·      Knowledge on Denodo, data cataloguing tools & data quality mechanisms is a plus.

·      Strong team player with good communication skills.

Overview Optisol Business Solutions

OptiSol was named on this year's Best Companies to Work for list by Great place to work. We are a team of about 500+ Agile employees with a development center in India and global offices in the US, UK (United Kingdom), Australia, Ireland, Sweden, and Dubai. 16+ years of joyful journey and we have built about 500+ digital solutions. We have 200+ happy and satisfied clients across 24 countries.

Benefits, working with Optisol

·      Great Learning & Development program

·      Flextime, Work-at-Home & Hybrid Options

·      A knowledgeable, high-achieving, experienced & fun team.

·      Spot Awards & Recognition.

·      The chance to be a part of next success story.

·      A competitive base salary.

More Than Just a Job, We Offer an Opportunity To Grow. Are you the one, who looks out to Build your Future & Build your Dream? We have the Job for you, to make your dream comes true.

Skills and requirements

• Experience analyzing complex and varied data in a commercial or academic setting.
• Desire to solve new and complex problems every day.
• Excellent ability to communicate scientific results to both technical and non-technical team members.

Desirable

• A degree in a numerically focused discipline such as, Maths, Physics, Chemistry, Engineering or Biological Sciences..
• Hands on experience on Python, Pyspark, SQL
• Hands on experience on building End to End Data Pipelines.
• Hands on Experience on Azure Data Factory, Azure Data Bricks, Data Lake - added advantage
• Hands on Experience in building data pipelines.
• Experience with Bigdata Tools, Hadoop, Hive, Sqoop, Spark, SparkSQL
• Experience with SQL or NoSQL databases for the purposes of data retrieval and management.
• Experience in data warehousing and business intelligence tools, techniques and technology, as well as experience in diving deep on data analysis or technical issues to come up with effective solutions.
• BS degree in math, statistics, computer science or equivalent technical field.
• Experience in data mining structured and unstructured data (SQL, ETL, data warehouse, Machine Learning etc.) in a business environment with large-scale, complex data sets.
• Proven ability to look at solutions in unconventional ways. Sees opportunities to innovate and can lead the way.
• Willing to learn and work on Data Science, ML, AI.

Job Summary

As a Data Science Lead, you will manage multiple consulting projects of varying complexity and ensure on-time and on-budget delivery for clients. You will lead a team of data scientists and collaborate across cross-functional groups, while contributing to new business development, supporting strategic business decisions and maintaining & strengthening client base

1. Work with team to define business requirements, come up with analytical solution and deliver the solution with specific focus on Big Picture to drive robustness of the solution
2. Work with teams of smart collaborators. Be responsible for their appraisals and career development.
3. Participate and lead executive presentations with client leadership stakeholders.
4. Be part of an inclusive and open environment. A culture where making mistakes and learning from them is part of life
5. See how your work contributes to building an organization and be able to drive Org level initiatives that will challenge and grow your capabilities.

​​​​​​Role & Responsibilities

1. Serve as expert in Data Science, build framework to develop Production level DS/AI models.
2. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients.
3. Lead multiple teams across clients ensuring quality and timely outcomes on all projects.
4. Lead and manage the onsite-offshore relation, at the same time adding value to the client.
5. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions.
6. Build a winning team focused on client success. Help team members build lasting career in data science and create a constant learning/development environment.
7. Present results, insights, and recommendations to senior management with an emphasis on the business impact.
8. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization.
9. Lead or contribute to org level initiatives to build the Tredence of tomorrow.

Qualification & Experience

1. Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Statistics, Data Science) or equivalent experience.
2. 6-10+ years of experience in data science, building hands-on ML models
3. Expertise in ML – Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning.
4. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA , Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers.
5. Knowledge of programming languages SQL, Python/ R, Spark.
6. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch).
7. Experience with cloud computing services (AWS, GCP or Azure)
8. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing
9. Knowledge in Mathematical programming – Linear Programming, Mixed Integer Programming etc , Stochastic Modelling – Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models.
10. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP)
11. Knowledge in GPU code optimization, Spark MLlib Optimization.
12. Familiarity to deploy and monitor ML models in production, delivering data products to end-users.
13. Experience with ML CI/CD pipelines.

• Analyze and organize raw data 
• Build data systems and pipelines
• Evaluate business needs and objectives
• Interpret trends and patterns
• Conduct complex data analysis and report on results 
• Build algorithms and prototypes
• Combine raw information from different sources
• Explore ways to enhance data quality and reliability
• Identify opportunities for data acquisition
• Should have experience in Python, Django Micro Service Senior developer with Financial Services/Investment Banking background.
• Develop analytical tools and programs
• Collaborate with data scientists and architects on several projects
• Should have 5+ years of experience as a data engineer or in a similar role
• Technical expertise with data models, data mining, and segmentation techniques
• Should have experience programming languages such as Python
• Hands-on experience with SQL database design
• Great numerical and analytical skills
• Degree in Computer Science, IT, or similar field; a Master’s is a plus
• Data engineering certification (e.g. IBM Certified Data Engineer) is a plus

We are looking for an outstanding Big Data Engineer with experience setting up and maintaining Data Warehouse and Data Lakes for an Organization. This role would closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Roles and Responsibilities:

• Develop and maintain scalable data pipelines and build out new integrations and processes required for optimal extraction, transformation, and loading of data from a wide variety of data sources using 'Big Data' technologies.
• Develop programs in Scala and Python as part of data cleaning and processing.
• Assemble large, complex data sets that meet functional / non-functional business requirements and fostering data-driven decision making across the organization.  
• Responsible to design and develop distributed, high volume, high velocity multi-threaded event processing systems.
• Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Provide high operational excellence guaranteeing high availability and platform stability.
• Closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Skills:

• Experience with Big Data pipeline, Big Data analytics, Data warehousing.
• Experience with SQL/No-SQL, schema design and dimensional data modeling.
• Strong understanding of Hadoop Architecture, HDFS ecosystem and eexperience with Big Data technology stack such as HBase, Hadoop, Hive, MapReduce.
• Experience in designing systems that process structured as well as unstructured data at large scale.
• Experience in AWS/Spark/Java/Scala/Python development.
• Should have Strong skills in PySpark (Python & SPARK). Ability to create, manage and manipulate Spark Dataframes. Expertise in Spark query tuning and performance optimization.
• Experience in developing efficient software code/frameworks for multiple use cases leveraging Python and big data technologies.
• Prior exposure to streaming data sources such as Kafka.
• Should have knowledge on Shell Scripting and Python scripting.
• High proficiency in database skills (e.g., Complex SQL), for data preparation, cleaning, and data wrangling/munging, with the ability to write advanced queries and create stored procedures.
• Experience with NoSQL databases such as Cassandra / MongoDB.
• Solid experience in all phases of Software Development Lifecycle - plan, design, develop, test, release, maintain and support, decommission.
• Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development).
• Experience building and deploying applications on on-premise and cloud-based infrastructure.
• Having a good understanding of machine learning landscape and concepts. 

Qualifications and Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Big Data Engineer or a similar role for 3-5 years.

Certifications:

Good to have at least one of the Certifications listed here:

    AZ 900 - Azure Fundamentals

    DP 200, DP 201, DP 203, AZ 204 - Data Engineering

    AZ 400 - Devops Certification

Key Responsibilities:

• Partnering with clients and internal business owners (product, marketing, edit, etc.) to understand needs and develop models and products for Kaleidofin business line.
• Good understanding of the underlying business and workings of cross functional teams for successful execution
• Design and develop analyses based on business requirement needs and challenges.
• Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, hyperparameter tuning, ensembling etc.
• Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
• Identify and use appropriate investigative and analytical technologies to interpret and verify results.
• Apply and learn a wide variety of tools and languages to achieve results
• Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.
• Collaborate with the team to improve the effectiveness of business decisions using data and machine learning/predictive modeling.
• Innovate on projects by using new modeling techniques or tools.
• Utilize effective project planning techniques to break down complex projects into tasks and ensure deadlines are kept.
• Communicate findings to team and leadership to ensure models are well understood and incorporated into business processes.

Skills:

• 2+ year experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
• Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, Boosting trees, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, ensemble methods.
• Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools
• Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
• Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE)
• Experience in risk and credit scoring domains preferred

Job Overview

                         We are looking for a ML Architect to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. They must have strong experience using variety of data mining and data analysis methods, building and implementing models, using/creating algorithm’s and creating/running simulations.  They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. Automating to identify the textual data with their properties and structure form various type of document.

Responsibilities

• Selecting features, building and optimizing classifiers using machine learning techniques
• Data mining using state-of-the-art methods
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis
• Creating automated anomaly detection systems and constant tracking of its performance
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Secure and manage when needed GPU cluster resources for events
• Write comprehensive internal feedback reports and find opportunities for improvements
• Manage GPU instances/machines to increase the performance and efficiency of the ML/DL model.

Skills and Qualifications

• Strong Hands-on experience in Python Programming
• Working experience with Computer Vision models - Object Detection Model, Image Classification
• Good experience in feature extraction, feature selection techniques and transfer learning
• Working Experience in building deep learning NLP Models for text classification, image analytics-CNN,RNN,LSTM.
• Working Experience in any of the AWS/GCP cloud platforms, exposure in fetching data from various sources.
• Good experience in exploratory data analysis, data visualisation, and other data preprocessing techniques.
• Knowledge in any one of the DL frameworks like Tensorflow, Pytorch, Keras, Caffe
• Good knowledge in statistics,distribution of data and in supervised and unsupervised machine learning algorithms.
• Exposure to OpenCV Familiarity with GPUs + CUDA
• Experience with NVIDIA software for cluster management and provisioning such as nvsm, dcgm and DeepOps.
• We are looking for a candidate with 14+ years of experience, 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 AWS cloud services: EC2, RDS, AWS-Sagemaker(Added advantage)
• Experience with object-oriented/object function scripting languages in any: Python, Java, C++, Scala, etc.