Senior Software Engineer

About Company

Our client is the worlds largest media investment company and a global digital transformation agency with 1200 employees across 21 nations. They support clients in programmatic, social, paid search, analytics, technology, organic search, affiliate marketing, e-commerce and across traditional channels

About The Role

· Provide support on Campaign Measurement, Brand Lift studies, Reporting and other data needs (ingestion, cleaning, delivery etc.)

· Code in SQL, Python to create reports and build dashboards.

· Use Bigquery, Python, Datalab (GCP) and automate recurring workloads to improve efficiency

· Maintain underlying data infrastructure and troubleshoot data issues

· Generate meaningful insights from data using advanced analytics/statistical techniques and create dashboards and presentations for wider teams.

· Liaise closely with clients (internally and externally) on projects and work with key stakeholders to assess project needs and ensure best-in-class work is being delivered.

A bit about yourself

· 0-2 years of experience required

· Programming skills in SQL, Python/R

· Logical thinking and problem solving skills

· Strong communication skills (verbal & written)

· Adherence to quality & ability to plan & prioritize the work

· Passionate about data analysis, ability to troubleshoot data anomalies, pulling data from several sources, integrating it to create data layers

· Experience in applying big data, statistics, analytical techniques and technology to solve client problems will be plus

· Experience in creating dashboards, reports, presentations and finding insights, and strong business acumen to provide actionable strategic recommendations will be plus.

About antuit.ai

Antuit.ai is the leader in AI-powered SaaS solutions for Demand Forecasting & Planning, Merchandising and Pricing. We have the industry’s first solution portfolio – powered by Artificial Intelligence and Machine Learning – that can help you digitally transform your Forecasting, Assortment, Pricing, and Personalization solutions. World-class retailers and consumer goods manufacturers leverage antuit.ai solutions, at scale, to drive outsized business results globally with higher sales, margin and sell-through.

Antuit.ai’s executives, comprised of industry leaders from McKinsey, Accenture, IBM, and SAS, and our team of Ph.Ds., data scientists, technologists, and domain experts, are passionate about delivering real value to our clients. Antuit.ai is funded by Goldman Sachs and Zodius Capital.

The Role:

Antuit.ai is interested in hiring a Principal Data Scientist, this person will facilitate standing up standardization and automation ecosystem for ML product delivery, he will also actively participate in managing implementation, design and tuning of product to meet business needs.

Responsibilities:

Responsibilities includes, but are not limited to the following:

• Manage and provides technical expertise to the delivery team. This includes recommendation of solution alternatives, identification of risks and managing business expectations.
• Design, build reliable and scalable automated processes for large scale machine learning.
• Use engineering expertise to help design solutions to novel problems in software development, data engineering, and machine learning. 
• Collaborate with Business, Technology and Product teams to stand-up MLOps process.
• Apply your experience in making intelligent, forward-thinking, technical decisions to delivery ML ecosystem, including implementing new standards, architecture design, and workflows tools.
• Deep dive into complex algorithmic and product issues in production
• Own metrics and reporting for delivery team. 
• Set a clear vision for the team members and working cohesively to attain it.
• Mentor and coach team members

Qualifications and Skills:

Requirements

• Engineering degree in any stream
• Has at least 7 years of prior experience in building ML driven products/solutions
• Excellent programming skills in any one of the language C++ or Python or Java.
• Hands on experience on open source libraries and frameworks- Tensorflow,Pytorch, MLFlow, KubeFlow, etc.
• Developed and productized large-scale models/algorithms in prior experience
• Can drive fast prototypes/proof of concept in evaluating various technology, frameworks/performance benchmarks.
• Familiar with software development practices/pipelines (DevOps- Kubernetes, docker containers, CI/CD tools).
• Good verbal, written and presentation skills.
• Ability to learn new skills and technologies.
• 3+ years working with retail or CPG preferred.
• Experience in forecasting and optimization problems, particularly in the CPG / Retail industry preferred.

Information Security Responsibilities

• Understand and adhere to Information Security policies, guidelines and procedure, practice them for protection of organizational data and Information System.
• Take part in Information Security training and act accordingly while handling information.
• Report all suspected security and policy breach to Infosec team or appropriate authority (CISO).

EEOC

DATA ENGINEER

Overview

They started with a singular belief - what is beautiful cannot and should not be defined in marketing meetings. It's defined by the regular people like us, our sisters, our next-door neighbours, and the friends we make on the playground and in lecture halls. That's why we stand for people-proving everything we do. From the inception of a product idea to testing the final formulations before launch, our consumers are a part of each and every process. They guide and inspire us by sharing their stories with us. They tell us not only about the product they need and the skincare issues they face but also the tales of their struggles, dreams and triumphs. Skincare goes deeper than skin. It's a form of self-care for many. Wherever someone is on this journey, we want to cheer them on through the products we make, the content we create and the conversations we have. What we wish to build is more than a brand. We want to build a community that grows and glows together - cheering each other on, sharing knowledge, and ensuring people always have access to skincare that really works.

Job Description:

We are seeking a skilled and motivated Data Engineer to join our team. As a Data Engineer, you will be responsible for designing, developing, and maintaining the data infrastructure and systems that enable efficient data collection, storage, processing, and analysis. You will collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to implement data pipelines and ensure the availability, reliability, and scalability of our data platform.

Responsibilities:

Design and implement scalable and robust data pipelines to collect, process, and store data from various sources.

Develop and maintain data warehouse and ETL (Extract, Transform, Load) processes for data integration and transformation.

Optimize and tune the performance of data systems to ensure efficient data processing and analysis.

Collaborate with data scientists and analysts to understand data requirements and implement solutions for data modeling and analysis.

Identify and resolve data quality issues, ensuring data accuracy, consistency, and completeness.

Implement and maintain data governance and security measures to protect sensitive data.

Monitor and troubleshoot data infrastructure, perform root cause analysis, and implement necessary fixes.

Stay up-to-date with emerging technologies and industry trends in data engineering and recommend their adoption when appropriate.

Qualifications:

Bachelor’s or higher degree in Computer Science, Information Systems, or a related field.

Proven experience as a Data Engineer or similar role, working with large-scale data processing and storage systems.

Strong programming skills in languages such as Python, Java, or Scala.

Experience with big data technologies and frameworks like Hadoop, Spark, or Kafka.

Proficiency in SQL and database management systems (e.g., MySQL, PostgreSQL, or Oracle).

Familiarity with cloud platforms like AWS, Azure, or GCP, and their data services (e.g., S3, Redshift, BigQuery).

Solid understanding of data modeling, data warehousing, and ETL principles.

Knowledge of data integration techniques and tools (e.g., Apache Nifi, Talend, or Informatica).

Strong problem-solving and analytical skills, with the ability to handle complex data challenges.

Excellent communication and collaboration skills to work effectively in a team environment.

Preferred Qualifications:

Advanced knowledge of distributed computing and parallel processing.

Experience with real-time data processing and streaming technologies (e.g., Apache Kafka, Apache Flink).

Familiarity with machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).

Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes).

Experience with data visualization and reporting tools (e.g., Tableau, Power BI).

Certification in relevant technologies or data engineering disciplines.

• Be the analytical expert in Kaleidofin, managing ambiguous problems by using data to execute sophisticated quantitative modeling and deliver actionable insights.
• Develop comprehensive skills including project management, business judgment, analytical problem solving and technical depth.
• Become an expert on data and trends, both internal and external to Kaleidofin.
• Communicate key state of the business metrics and develop dashboards to enable teams to understand business metrics independently.
• Collaborate with stakeholders across teams to drive data analysis for key business questions, communicate insights and drive the planning process with company executives.
• Automate scheduling and distribution of reports and support auditing and value realization.
• Partner with enterprise architects to define and ensure proposed.
• Business Intelligence solutions adhere to an enterprise reference architecture.
• Design robust data-centric solutions and architecture that incorporates technology and strong BI solutions to scale up and eliminate repetitive tasks.

• Experience leading development efforts through all phases of SDLC.
• 2+ years "hands-on" experience designing Analytics and Business Intelligence solutions.
• Experience with Quicksight, PowerBI, Tableau and Qlik is a plus.
• Hands on experience in SQL, data management, and scripting (preferably Python).
• Strong data visualisation design skills, data modeling and inference skills.
• Hands-on and experience in managing small teams.
• Financial services experience preferred, but not mandatory.
• Strong knowledge of architectural principles, tools, frameworks, and best practices.
• Excellent communication and presentation skills to communicate and collaborate with all levels of the organisation.
• Preferred candidates with less than 30 days notice period.

Responsibilities:

• Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world.
• Verifying data quality, and/or ensuring it via data cleaning.
• Able to adapt and work fast in producing the output which upgrades the decision making of stakeholders using ML.
• To design and develop Machine Learning systems and schemes. 
• To perform statistical analysis and fine-tune models using test results.
• To train and retrain ML systems and models as and when necessary. 
• To deploy ML models in production and maintain the cost of cloud infrastructure.
• To develop Machine Learning apps according to client and data scientist requirements.
• To analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by how successful they are in meeting the objective.

Technical Knowledge:

• Worked with real time problems, solved them using ML and deep learning models deployed in real time and should have some awesome projects under his belt to showcase. 
• Proficiency in Python and experience with working with Jupyter Framework, Google collab and cloud hosted notebooks such as AWS sagemaker, DataBricks etc.
• Proficiency in working with libraries Sklearn, Tensorflow, Open CV2, Pyspark,  Pandas, Numpy and related libraries.
• Expert in visualising and manipulating complex datasets.
• Proficiency in working with visualisation libraries such as seaborn, plotly, matplotlib etc.
• Proficiency in Linear Algebra, statistics and probability required for Machine Learning.
• Proficiency in ML Based algorithms for example, Gradient boosting, stacked Machine learning, classification algorithms and deep learning algorithms. Need to have experience in hypertuning various models and comparing the results of algorithm performance.
• Big data Technologies such as Hadoop stack and Spark. 
• Basic use of clouds (VM’s example EC2).
• Brownie points for Kubernetes and Task Queues.      
• Strong written and verbal communications.
• Experience working in an Agile environment.