Thoucentric - Applied Machine Learning Scientist (3-8 yrs)

About Us :

Thoucentric is the Consulting arm of Xoriant, a prominent digital engineering services company with 5000+ employees. We are headquartered in Bangalore with presence across multiple locations in India, US, UK, Singapore & Australia Globally.

As the Consulting business of Xoriant, We help clients with Business Consulting, Program & Project Management, Digital Transformation, Product Management, Process & Technology Solutioning and Execution including Analytics & Emerging Tech areas cutting across functional areas such as Supply Chain, Finance & HR, Sales & Distribution across US, UK, Singapore and Australia. Our unique consulting framework allows us to focus on execution rather than pure advisory. We are working closely with marquee names in the global consumer & packaged goods (CPG) industry, new age tech and start-up ecosystem. Xoriant (Parent entity) started in 1990 and is a Sunnyvale, CA headquartered digital engineering firm with offices in the USA, Europe, and Asia. Xoriant is backed by ChrysCapital, a leading private equity firm. Our strengths are now combined with Xoriants capabilities in AI & Data, cloud, security and operations services proven for 30 years.

We have been certified as "Great Place to Work" by AIM and have been ranked as "50 Best Firms for Data Scientists to Work For".

We have an experienced consulting team of over 450+ world-class business and technology consultants based across six global locations, supporting clients through their expert insights, entrepreneurial approach and focus on delivery excellence. We have also built point solutions and products through Thoucentric labs using AI/ML in the supply chain space.

Job Description :

Applied Machine Learning Scientist with a strong foundation in advanced machine learning techniques, expertise in time-series analysis, and experience in deploying solutions in cloud environments. This role requires someone who can develop, implement, and optimize machine learning pipelines that deliver business impact, collaborating closely with clients and product team to tailor solutions to their unique needs.

Key Responsibilities :

- Algorithm Design and Implementation : Develop and apply advanced machine learning models, with a focus on time regression, time series analysis, and classification algorithms. Evaluate the suitability of different algorithms and choose the best approach for each problem.

- Exploratory Data Analysis (EDA) : Perform in-depth exploratory data analysis to gain insights, drive feature engineering, and inform model design.

- Solution Strategy and Client Collaboration : Work directly with clients to understand their business challenges, advising on solution approaches and designing machine learning strategies that meet their objectives.

- Production-Ready Code and Pipeline Deployment : Write efficient, production-grade Python code, with a focus on scalable solutions. Implement machine learning solutions as cloud-based pipelines, ensuring seamless deployment, integration, and reproducibility.

- Cloud Platform Expertise : Design, deploy, and manage machine learning pipelines on cloud platforms (e.g., AWS, Azure, GCP), leveraging cloud services for storage, computation, and model management.

- Debugging, Optimization, and Best Practices : Troubleshoot, debug, and optimize code to ensure it meets production standards. Follow programming best practices, including object-oriented programming (OOP) principles, version control, and documentation.

- Result Analysis and Communication : Analyze model results, derive insights, and present findings to both technical and non-technical stakeholders in a clear, actionable format.

Requirements :

Required Skills and Qualifications :

- Machine Learning Expertise : Strong experience with machine learning and deep learning algorithms, across regression, time series, and classification problems. Deep understanding of the nuances and applications of each.

- Python and OOP : Advanced proficiency in Python programming, with a strong understanding of object-oriented programming concepts and clean coding practices.

- Cloud Platform Proficiency : Hands-on experience with cloud platforms (AWS, Azure, GCP) for deploying and managing machine learning solutions. Familiarity with services for data storage, model deployment, and workflow automation.

- Pipeline Development and Deployment : Experience building, deploying, and monitoring end-to-end machine learning pipelines on cloud environments, ensuring reliable and scalable solutions.

- Debugging and Optimization : Excellent debugging skills, with an ability to identify performance bottlenecks, optimize code, and enhance model accuracy.

- Client Engagement : Proven ability to communicate with clients, understand their needs, and explain technical solutions in an accessible manner.

Preferred Qualifications :

- Big Data Tools : Familiarity with big data tools and distributed computing frameworks (e.g., Spark, databricks) is a plus.

- Problem-Solving Mindset : Strong analytical and creative problem-solving skills with a proactive, solution-focused approach.

This role is ideal for a motivated ML Scientist who can deliver technical excellence and impactful solutions through cloud-based deployments. If you are passionate about solving complex data challenges and are ready to drive innovation, we encourage you to apply.

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