295 Data Science jobs in Hyderabad

Company Brief

House of Shipping provides business consultancy and advisory services for Shipping & Logistics companies. House of Shipping's commitment to their customers begins with developing an understanding of their business fundamentals. We are hiring on behalf of one of our key US based client - a globally recognized service provider of flexible and scalable outsourced warehousing solutions, designed to adapt to the evolving demands of today’s supply chains.

Currently House of Shipping is looking to identify a high caliber Data Science Lead.

This position is an on-site position for Hyderabad.

Background and experience:

• 15–18 years in data science, with 5+ years in leadership roles
• Proven track record in building and scaling data science teams in logistics, e-commerce, or manufacturing
• Strong understanding of statistical learning, ML architecture, productionizing models, and impact tracking

Job purpose:

To lead enterprise-scale data science initiatives in supply chain optimization, forecasting, network analytics, and predictive maintenance. This role blends technical leadership with strategic alignment across business units and manages advanced analytics teams to deliver measurable business impact.

Main tasks and responsibilities:

• Define and drive the data science roadmap across forecasting (demand, returns), route optimization, warehouse simulation, inventory management, and fraud detection
• Architect end-to-end pipelines with engineering teams: from data ingestion, model development, to API deployment
• Lead the design and deployment of ML models using Python (Scikit-Learn, XGBoost, PyTorch, LightGBM), and MLOps tools like MLflow, Vertex AI, or AWS SageMaker
• Collaborate with operations, product, and technology to prioritize AI use cases and define business metrics
• Manage experimentation frameworks (A/B testing, simulation models) and statistical hypothesis testing
• Mentor team members in model explainability, interpretability, and ethical AI practices
• Ensure robust model validation, drift monitoring, retraining schedules, and version control
• Contribute to organizational data maturity: feature stores, reusable components, metadata tracking
• Own team hiring, capability development, project estimation, and stakeholder presentations
• Collaborate with external vendors, universities, and open-source projects where applicable

Education requirements:

Bachelor’s or Master’s or PhD in Computer Science, Mathematics, Statistics, Operations Research

Preferred: Certifications in Cloud ML stacks (AWS/GCP/Azure), MLOps, or Applied AI

Competencies and skills:

• Strategic vision in AI applications across supply chain
• Team mentorship and delivery ownership
• Expertise in statistical and ML frameworks
• MLOps pipeline management and deployment best practices
• Strong business alignment and executive communication

Job Code: BTL-2507105

Job title: Data Science Intern

Experience : Fresher

Mode : Work From Office

Location : Hyderabad

Duration: 6 Months

Stipend : 3 months unpaid and another 3 months paid

Website :

LinkedIn Page:

Responsibilities:

• Assist in the development and implementation of data-driven solutions to complex business problems.
• Conduct data analysis and modelling to identify trends, patterns, and insights.
• Clean, prepare, and process large datasets for analysis.
• Collaborate with cross-functional teams to identify and optimise business opportunities.
• Develop and maintain data pipelines and tools for efficient data ingestion, processing, and visualisation.
• Present findings and recommendations to key stakeholders in a clear and concise manner.
• Stay informed on the latest trends and advancements in the field of data science.

Requirements:

• Should be familiar with NLP, Generative AI, LLMs, RAG (preferable)
• Strong analytical thinking and problem-solving skills.
• Proficiency in programming languages such as Python and R.
• Knowledge of Pandas, Scikit learn, Tensorflow. PyTorch.
• Experience with data preprocessing, cleansing, and validation techniques.
• Familiarity with data visualization tools and libraries.
• Strong written and verbal communication skills.
• Ability to work independently and collaboratively in a fast-paced environment.
• Attention to detail and ability to handle multiple projects simultaneously.

Education:

• Currently pursuing a Bachelor's or Master's degree in (Data Science / Computer Science / Statistics / or a related field.

Benefits

• Opportunity to learn from experienced professionals.
• Exposure to real-world projects.
• Potential for full-time employment after successful completion of the internship.

About the Role:

We are seeking a highly experienced Voice AI /ML Engineer to lead the design and

deployment of real-time voice intelligence systems. This role focuses on ASR, TTS, speaker

diarization, wake word detection, and building production-grade modular audio processing

pipelines to power next-generation contact centre solutions, intelligent voice agents, and

telecom-grade audio systems.

You will work at the intersection of deep learning, streaming infrastructure, and

speech/NLP technology, creating scalable, low-latency systems across diverse audio formats

and real-world applications.

Key Responsibilities:

Voice & Audio Intelligence:

 Build, fine-tune, and deploy ASR models (e.g., Whisper, wav2vec2.0, Conformer) for

real-time transcription.

Develop and finetune high-quality TTS systems using VITS, Tacotron, FastSpeech for

lifelike voice generation and cloning.

mplement speaker diarization for segmenting and identifying speakers in multi-party

conversations using embeddings (x-vectors/d-vectors) and clustering (AHC, VBx, spectral

clustering).

esign robust wake word detection models with ultra-low latency and high accuracy in

noisy conditions.

Real-Time Audio Streaming & Voice Agent Infrastructure:

rchitect bi-directional real-time audio streaming pipelines using WebSocket, gRPC,

Twilio Media Streams, or WebRTC.

ntegrate voice AI models into live voice agent solutions, IVR automation, and AI

contact center platforms.

ptimize for latency, concurrency, and continuous audio streaming with context

buffering and voice activity detection (VAD).

uild scalable microservices to process, decode, encode, and stream audio across

common codecs (e.g., PCM, Opus, μ-law, AAC, MP3) and containers (e.g., WAV, MP4).

Deep Learning & NLP Architecture:

 ilize transformers, encoder-decoder models, GANs, VAEs, and diffusion models, for

speech and language tasks.

mplement end-to-end pipelines including text normalization, G2P mapping, NLP intent

extraction, and emotion/prosody control.

ine-tune pre-trained language models for integration with voice-based user interfaces.

Modular System Development:

uild reusable, plug-and-play modules for ASR, TTS, diarization, codecs, streaming

inference, and data augmentation.

esign APIs and interfaces for orchestrating voice tasks across multi-stage pipelines with

format conversions and buffering.

evelop performance benchmarks and optimize for CPU/GPU, memory footprint, and

real-time constraints.

Engineering & Deployment:

riting robust, modular, and efficient Python code

xperience with Docker, Kubernetes, cloud deployment (AWS, Azure, GCP)

ptimize models for real-time inference using ONNX, TorchScript, and CUDA, including

quantization, context-aware inference, model caching.

n device voice model deployment.

Why join us?

mpactful Work: Play a pivotal role in safeguarding Tanla's assets, data, and reputation

in the industry.

remendous Growth Opportunities: Be part of a rapidly growing company in the

telecom and CPaaS space, with opportunities for professional development.

nnovative Environment: Work alongside a world-class team in a challenging and fun

environment, where innovation is celebrated.

Tanla is an equal opportunity employer. We champion diversity and are committed to

creating an inclusive environment for all employees.

About the Role:

We are seeking a highly experienced Voice AI /ML Engineer to lead the design and

deployment of real-time voice intelligence systems. This role focuses on ASR, TTS, speaker

diarization, wake word detection, and building production-grade modular audio processing

pipelines to power next-generation contact centre solutions, intelligent voice agents, and

telecom-grade audio systems.

You will work at the intersection of deep learning, streaming infrastructure, and

speech/NLP technology, creating scalable, low-latency systems across diverse audio formats

and real-world applications.

Key Responsibilities:

Voice & Audio Intelligence:

 Build, fine-tune, and deploy ASR models (e.g., Whisper, wav2vec2.0, Conformer) for

real-time transcription.

Develop and finetune high-quality TTS systems using VITS, Tacotron, FastSpeech for

lifelike voice generation and cloning.

mplement speaker diarization for segmenting and identifying speakers in multi-party

conversations using embeddings (x-vectors/d-vectors) and clustering (AHC, VBx, spectral

clustering).

esign robust wake word detection models with ultra-low latency and high accuracy in

noisy conditions.

Real-Time Audio Streaming & Voice Agent Infrastructure:

rchitect bi-directional real-time audio streaming pipelines using WebSocket, gRPC,

Twilio Media Streams, or WebRTC.

ntegrate voice AI models into live voice agent solutions, IVR automation, and AI

contact center platforms.

ptimize for latency, concurrency, and continuous audio streaming with context

buffering and voice activity detection (VAD).

uild scalable microservices to process, decode, encode, and stream audio across

common codecs (e.g., PCM, Opus, μ-law, AAC, MP3) and containers (e.g., WAV, MP4).

Deep Learning & NLP Architecture:

 ilize transformers, encoder-decoder models, GANs, VAEs, and diffusion models, for

speech and language tasks.

mplement end-to-end pipelines including text normalization, G2P mapping, NLP intent

extraction, and emotion/prosody control.

ine-tune pre-trained language models for integration with voice-based user interfaces.

Modular System Development:

uild reusable, plug-and-play modules for ASR, TTS, diarization, codecs, streaming

inference, and data augmentation.

esign APIs and interfaces for orchestrating voice tasks across multi-stage pipelines with

format conversions and buffering.

evelop performance benchmarks and optimize for CPU/GPU, memory footprint, and

real-time constraints.

Engineering & Deployment:

riting robust, modular, and efficient Python code

xperience with Docker, Kubernetes, cloud deployment (AWS, Azure, GCP)

ptimize models for real-time inference using ONNX, TorchScript, and CUDA, including

quantization, context-aware inference, model caching.

n device voice model deployment.

Why join us?

mpactful Work: Play a pivotal role in safeguarding Tanla's assets, data, and reputation

in the industry.

remendous Growth Opportunities: Be part of a rapidly growing company in the

telecom and CPaaS space, with opportunities for professional development.

nnovative Environment: Work alongside a world-class team in a challenging and fun

environment, where innovation is celebrated.

Tanla is an equal opportunity employer. We champion diversity and are committed to

creating an inclusive environment for all employees.