Data Scientist

Job Description

Responsibilities:

- Collaborate with stakeholders to understand business objectives and requirements for AI/ML projects.

- Conduct research and stay up-to-date with the latest AI/ML algorithms, techniques, and frameworks.

- Design and develop machine learning models, algorithms, and data pipelines.

- Collect, preprocess, and clean large datasets to ensure data quality and reliability.

- Train, evaluate, and optimize machine learning models using appropriate evaluation metrics.

- Implement and deploy AI/ML models into production environments.

- Monitor model performance and propose enhancements or updates as needed.

- Collaborate with software engineers to integrate AI/ML capabilities into existing software systems.

- Perform data analysis and visualization to derive actionable insights.

- Stay informed about emerging trends and advancements in the field of AI/ML and apply them to improve existing solutions.

Strong experience in Apache pyspark is must

Requirements:

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- Proven experience of 3-5 years as an AI/ML Engineer or a similar role.

- Strong knowledge of machine learning algorithms, deep learning frameworks, and data science concepts.

- Proficiency in programming languages such as Python, Java, or C++.

- Experience with popular AI/ML libraries and frameworks, such as TensorFlow, Keras, PyTorch, or scikit-learn.

- Familiarity with cloud platforms, such as AWS, Azure, or GCP, and their AI/ML services.

- Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.

- Experience in deploying and scaling machine learning models in production environments.

- Strong problem-solving skills and ability to work on multiple projects simultaneously.

- Excellent communication and teamwork skills.

Preferred Skills:

- Experience with natural language processing (NLP) techniques and tools.

- Familiarity with big data technologies, such as Hadoop, Spark, or Hive.

- Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.

- Understanding of DevOps practices for AI/ML model deployment

-Apache ,Pyspark

Strong Power Bi, Power App and SQL skills,

• Design and build compelling analyses, trending and/or forecasting reports using Microsoft Power BI.

• Design and build apps using power apps and power automate.

• Assist in the publishing of metrics dashboards by identifying, analyzing and interpreting trends or patterns in complex data sets.

• Define BI development objectives by analyzing user requirements while envisioning system features and functionality.

• Translate business needs into technical requirements, clearly communicate probable designs and create prototypes.

• Follow data and reporting performance optimization and tuning best practices.

• Conduct analytical activities of system data.

• Conducts complex data analysis and evaluates intangibles providing management with fact-based information.

• Knowledge of the supply chain domain.

• Proven, effective analytical skills

• Ability to work effectively under time constraints and multitask.

• Ability to work collaboratively across multiple functions and departments within the organization.

Requirement understanding and elicitation, analysis, data/workflows, contribution to product

projects and Proof of concept (POC)

 Contribute to preparing design documents and effort estimations.

 Develop AI/ML Models using best-in-class ML models.

 Building, testing, and deploying AI/ML solutions.

 Work with Business Analysts and Product Managers to assist with defining functional user

stories.

 Ensure deliverables across teams are of high quality and documented. 

 Recommend best ML practices/Industry standards for any ML use case.

 Proactively take up R and D and recommend solution options for any ML use case.

Mactores is a trusted leader among businesses in providing modern data platform solutions. Since 2008, Mactores have been enabling businesses to accelerate their value through automation by providing End-to-End Data Solutions that are automated, agile, and secure. We collaborate with customers to strategize, navigate, and accelerate an ideal path forward with a digital transformation via assessments, migration, or modernization.

We are looking for a DataOps Engineer with expertise while operating a data lake. Amazon S3, Amazon EMR, and Apache Airflow for workflow management are used to build the data lake.

You have experience of building and running data lake platforms on AWS. You have exposure to operating PySpark-based ETL Jobs in Apache Airflow and Amazon EMR. Expertise in monitoring services like Amazon CloudWatch.

If you love solving problems using yo, professional services background, usual and fun office environment that actively steers clear of rigid "corporate" culture, focuses on productivity and creativity, and allows you to be part of a world-class team while still being yourself.

What you will do?

• Operate the current data lake deployed on AWS with Amazon S3, Amazon EMR, and Apache Airflow
• Debug and fix production issues in PySpark.
• Determine the RCA (Root cause analysis) for production issues.
• Collaborate with product teams for L3/L4 production issues in PySpark.
• Contribute to enhancing the ETL efficiency
• Build CloudWatch dashboards for optimizing the operational efficiencies
• Handle escalation tickets from L1 Monitoring engineers
• Assign the tickets to L1 engineers based on their expertise

What are we looking for?

• AWS data Ops engineer.
• Overall 5+ years of exp in the software industry Exp in developing architecture data applications using python or scala, Airflow, and Kafka on AWS Data platform Experience and expertise.
• Must have set up or led the project to enable Data Ops on AWS or any other cloud data platform.
• Strong data engineering experience on Cloud platform, preferably AWS.
• Experience with data pipelines designed for reuse and use parameterization.
• Experience of pipelines was designed to solve common ETL problems.
• Understanding or experience on various AWS services can be codified for enabling DataOps like Amazon EMR, Apache Airflow.
• Experience in building data pipelines using CI/CD infrastructure.
• Understanding of Infrastructure as code for DataOps ennoblement.
• Ability to work with ambiguity and create quick PoCs.

You will be preferred if

• Expertise in Amazon EMR, Apache Airflow, Terraform, CloudWatch
• Exposure to MLOps using Amazon Sagemaker is a plus.
• AWS Solutions Architect Professional or Associate Level Certificate
• AWS DevOps Professional Certificate

Life at Mactores

We care about creating a culture that makes a real difference in the lives of every Mactorian. Our 10 Core Leadership Principles that honor Decision-making, Leadership, Collaboration, and Curiosity drive how we work.

1. Be one step ahead

2. Deliver the best

3. Be bold

4. Pay attention to the detail

5. Enjoy the challenge

6. Be curious and take action

7. Take leadership

8. Own it

9. Deliver value

10. Be collaborative

We would like you to read more details about the work culture on https://mactores.com/careers 

The Path to Joining the Mactores Team

At Mactores, our recruitment process is structured around three distinct stages:

Pre-Employment Assessment: 

You will be invited to participate in a series of pre-employment evaluations to assess your technical proficiency and suitability for the role.

Managerial Interview: The hiring manager will engage with you in multiple discussions, lasting anywhere from 30 minutes to an hour, to assess your technical skills, hands-on experience, leadership potential, and communication abilities.

HR Discussion: During this 30-minute session, you'll have the opportunity to discuss the offer and next steps with a member of the HR team.

At Mactores, we are committed to providing equal opportunities in all of our employment practices, and we do not discriminate based on race, religion, gender, national origin, age, disability, marital status, military status, genetic information, or any other category protected by federal, state, and local laws. This policy extends to all aspects of the employment relationship, including recruitment, compensation, promotions, transfers, disciplinary action, layoff, training, and social and recreational programs. All employment decisions will be made in compliance with these principles.

Job Description for :

Role: Data/Integration Architect

Experience – 8-10 Years

Notice Period: Under 30 days

Key Responsibilities: Designing, Developing frameworks for batch and real time jobs on Talend. Leading migration of these jobs from Mulesoft to Talend, maintaining best practices for the team, conducting code reviews and demos.

Core Skillsets:

Talend Data Fabric - Application, API Integration, Data Integration. Knowledge on Talend Management Cloud, deployment and scheduling of jobs using TMC or Autosys.

Programming Languages - Python/Java
Databases: SQL Server, Other Databases, Hadoop

Should have worked on Agile

Sound communication skills

Should be open to learning new technologies based on business needs on the job

Additional Skills:

Awareness of other data/integration platforms like Mulesoft, Camel

Awareness Hadoop, Snowflake, S3

ears of Exp: 3-6+ Years 
Skills: Scala, Python, Hive, Airflow, Spark

Languages: Java, Python, Shell Scripting

GCP: BigTable, DataProc,  BigQuery, GCS, Pubsub

OR
AWS: Athena, Glue, EMR, S3, Redshift

MongoDB, MySQL, Kafka

Platforms: Cloudera / Hortonworks
AdTech domain experience is a plus.
Job Type - Full Time 

Responsibilities

• Own the design, development, testing, deployment, and craftsmanship of the team’s infrastructure and systems capable of handling massive amounts of requests with high reliability and scalability
• Leverage the deep and broad technical expertise to mentor engineers and provide leadership on resolving complex technology issues
• Entrepreneurial and out-of-box thinking essential for a technology startup
• Guide the team for unit-test code for robustness, including edge cases, usability, and general reliability

Requirements

• In-depth understanding of image processing algorithms, pattern recognition methods, and rule-based classifiers
• Experience in feature extraction, object recognition and tracking, image registration, noise reduction, image calibration, and correction
• Ability to understand, optimize and debug imaging algorithms
• Understating and experience in openCV library
• Fundamental understanding of mathematical techniques involved in ML and DL schemas (Instance-based methods, Boosting methods, PGM, Neural Networks etc.)
• Thorough understanding of state-of-the-art DL concepts (Sequence modeling, Attention, Convolution etc.) along with knack to imagine new schemas that work for the given data.
• Understanding of engineering principles and a clear understanding of data structures and algorithms
• Experience in writing production level codes using either C++ or Java
• Experience with technologies/libraries such as python pandas, numpy, scipy
• Experience with tensorflow and scikit.

• Proficient in R and Python
• Work experience 1+ years with at least 6 months working with Python
• Prior experience with building ML models
• Prior experience with SQL
• Knowledge of statistical techniques
• Experience with working on Spatial Data will be an added advantage