11+ Econometrics Jobs in Chennai | Econometrics Job openings in Chennai

Skills: Machine Learning,Deep Learning,Artificial Intelligence,python.

Location:Chennai


Domain knowledge: Data cleaning, modelling, analytics, statistics, machine learning, AI

Requirements:

·         To be part of Digital Manufacturing and Industrie 4.0 projects across Saint Gobain group of companies

·         Design and develop AI//ML models to be deployed across SG factories

·         Knowledge on Hadoop, Apache Spark, MapReduce, Scala, Python programming, SQL and NoSQL databases is required

·         Should be strong in statistics, data analysis, data modelling, machine learning techniques and Neural Networks

·         Prior experience in developing AI and ML models is required

·         Experience with data from the Manufacturing Industry would be a plus

Roles and Responsibilities:

·         Develop AI and ML models for the Manufacturing Industry with a focus on Energy, Asset Performance Optimization and Logistics

·         Multitasking, good communication necessary

·         Entrepreneurial attitude.

Position Overview: We are seeking a talented Data Engineer with expertise in Power BI to join our team. The ideal candidate will be responsible for designing and implementing data pipelines, as well as developing insightful visualizations and reports using Power BI. Additionally, the candidate should have strong skills in Python, data analytics, PySpark, and Databricks. This role requires a blend of technical expertise, analytical thinking, and effective communication skills.

Key Responsibilities:

1. Design, develop, and maintain data pipelines and architectures using PySpark and Databricks.
2. Implement ETL processes to extract, transform, and load data from various sources into data warehouses or data lakes.
3. Collaborate with data analysts and business stakeholders to understand data requirements and translate them into actionable insights.
4. Develop interactive dashboards, reports, and visualizations using Power BI to communicate key metrics and trends.
5. Optimize and tune data pipelines for performance, scalability, and reliability.
6. Monitor and troubleshoot data infrastructure to ensure data quality, integrity, and availability.
7. Implement security measures and best practices to protect sensitive data.
8. Stay updated with emerging technologies and best practices in data engineering and data visualization.
9. Document processes, workflows, and configurations to maintain a comprehensive knowledge base.

Requirements:

1. Bachelor’s degree in Computer Science, Engineering, or related field. (Master’s degree preferred)
2. Proven experience as a Data Engineer with expertise in Power BI, Python, PySpark, and Databricks.
3. Strong proficiency in Power BI, including data modeling, DAX calculations, and creating interactive reports and dashboards.
4. Solid understanding of data analytics concepts and techniques.
5. Experience working with Big Data technologies such as Hadoop, Spark, or Kafka.
6. Proficiency in programming languages such as Python and SQL.
7. Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud.
8. Excellent analytical and problem-solving skills with attention to detail.
9. Strong communication and collaboration skills to work effectively with cross-functional teams.
10. Ability to work independently and manage multiple tasks simultaneously in a fast-paced environment.

Preferred Qualifications:

• Advanced degree in Computer Science, Engineering, or related field.
• Certifications in Power BI or related technologies.
• Experience with data visualization tools other than Power BI (e.g., Tableau, QlikView).
• Knowledge of machine learning concepts and frameworks.

Design, implement, and improve the analytics platform

Implement and simplify self-service data query and analysis capabilities of the BI platform

Develop and improve the current BI architecture, emphasizing data security, data quality

and timeliness, scalability, and extensibility

Deploy and use various big data technologies and run pilots to design low latency

data architectures at scale

Collaborate with business analysts, data scientists, product managers, software development engineers,

and other BI teams to develop, implement, and validate KPIs, statistical analyses, data profiling, prediction,

forecasting, clustering, and machine learning algorithms

Educational

At Ganit we are building an elite team, ergo we are seeking candidates who possess the

following backgrounds:

7+ years relevant experience

Expert level skills writing and optimizing complex SQL

Knowledge of data warehousing concepts

Experience in data mining, profiling, and analysis

Experience with complex data modelling, ETL design, and using large databases

in a business environment

Proficiency with Linux command line and systems administration

Experience with languages like Python/Java/Scala

Experience with Big Data technologies such as Hive/Spark

Proven ability to develop unconventional solutions, sees opportunities to

innovate and leads the way

Good experience of working in cloud platforms like AWS, GCP & Azure. Having worked on

projects involving creation of data lake or data warehouse

Excellent verbal and written communication.

Proven interpersonal skills and ability to convey key insights from complex analyses in

summarized business terms. Ability to effectively communicate with multiple teams

Good to have

AWS/GCP/Azure Data Engineer Certification

• Partnering with internal business owners (product, marketing, edit, etc.) to understand needs and develop custom analysis to optimize for user engagement and retention
• 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, 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.

• 2 - 4 years  of relevant experience in Data science.
• Preferred education: Bachelor's degree in a technical field or equivalent experience.
• 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, XGBoost, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, boosting and 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 score domains preferred.

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.

Ganit Inc. is the fastest growing Data Science & AI company in Chennai.

Founded in 2017, by 3 industry experts who are alumnus of IITs/SPJIMR with each of them having 17+ years of experience in the field of analytics.

We are in the business of maximising Decision Making Power (DMP) for companies by providing solutions at the intersection of hypothesis based analytics, discovery based AI and IoT. Our solutions are a combination of customised services and functional product suite.

We primarily operate as a US-based start-up and have clients across US, Asia-Pacific, Middle-East and have offices in USA - New Jersey & India - Chennai.

Started with 3 people, the company is fast growing with 100+ employees

1. What do we expect from you

- Should posses minimum 2 years of experience of data analytics model development and deployment

- Skills relating to core Statistics & Mathematics.

- Huge interest in handling numbers

- Ability to understand all domains in businesses across various sectors

- Natural passion towards numbers, business, coding, visualisation

2. Necessary skill set:

- Proficient in R/Python, Advanced Excel, SQL

- Should have worked with Retail/FMCG/CPG projects solving analytical problems in Sales/Marketing/Supply Chain functions

- Very good understanding of algorithms, mathematical models, statistical techniques, data mining, like Regression models, Clustering/ Segmentation, time series forecasting, Decision trees/Random forest, etc.

- Ability to choose the right model for the right data and translate that into code in R, Python, VBA (Proven capabilities)

- Should have handled large datasets and with through understanding of SQL

- Ability to handle a team of Data Analysts

3. Good to have skill set:

- Microsoft PowerBI / Tableau / Qlik View / Spotfire

4. Job Responsibilities:

- Translate business requirements into technical requirements

- Data extraction, preparation and transformation

- Identify, develop and implement statistical techniques and algorithms that address business challenges and adds value to the organisation

- Create and implement data models

- Interact with clients for queries and delivery adoption

5. Screening Methodology

- Problem Solving round (Telephonic Conversation)

- Technical discussion round (Telephonic Conversation)

- Final fitment discussion (Video Round