4+ Pattern recognition Jobs in India

Data Scientist

Job Id: QX003

About Us:

QX impact was launched with a mission to make AI accessible and affordable and deliver AI Products/Solutions at scale for enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights, businesses will continue to face challenges to better understand their customers and even lose them; Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.

Position Overview:

We are seeking a collaborative and analytical Data Scientist who can bridge the gap between business needs and data science capabilities. In this role, you will lead and support projects that apply machine learning, AI, and statistical modeling to generate actionable insights and drive business value.

Key Responsibilities:

• Collaborate with stakeholders to define and translate business challenges into data science solutions.
• Conduct in-depth data analysis on structured and unstructured datasets.
• Build, validate, and deploy machine learning models to solve real-world problems.
• Develop clear visualizations and presentations to communicate insights.
• Drive end-to-end project delivery, from exploration to production.
• Contribute to team knowledge sharing and mentorship activities.

Must-Have Skills:

• 3+ years of progressive experience in data science, applied analytics, or a related quantitative role, demonstrating a proven track record of delivering impactful data-driven solutions.
• Exceptional programming proficiency in Python, including extensive experience with core libraries such as Pandas, NumPy, Scikit-learn, NLTK and XGBoost. 
• Expert-level SQL skills for complex data extraction, transformation, and analysis from various relational databases.
• Deep understanding and practical application of statistical modeling and machine learning techniques, including but not limited to regression, classification, clustering, time series analysis, and dimensionality reduction.
• Proven expertise in end-to-end machine learning model development lifecycle, including robust feature engineering, rigorous model validation and evaluation (e.g., A/B testing), and model deployment strategies.
• Demonstrated ability to translate complex business problems into actionable analytical frameworks and data science solutions, driving measurable business outcomes.
• Proficiency in advanced data analysis techniques, including Exploratory Data Analysis (EDA), customer segmentation (e.g., RFM analysis), and cohort analysis, to uncover actionable insights.
• Experience in designing and implementing data models, including logical and physical data modeling, and developing source-to-target mappings for robust data pipelines.
• Exceptional communication skills, with the ability to clearly articulate complex technical findings, methodologies, and recommendations to diverse business stakeholders (both technical and non-technical audiences).
• Experience in designing and implementing data models, including logical and physical data modeling, and developing source-to-target mappings for robust data pipelines.
• Exceptional communication skills, with the ability to clearly articulate complex technical findings, methodologies, and recommendations to diverse business stakeholders (both technical and non-technical audiences).

Good-to-Have Skills:

• Experience with cloud platforms (Azure, AWS, GCP) and specific services like Azure ML, Synapse, Azure Kubernetes and Databricks.
• Familiarity with big data processing tools like Apache Spark or Hadoop.
• Exposure to MLOps tools and practices (e.g., MLflow, Docker, Kubeflow) for model lifecycle management.
• Knowledge of deep learning libraries (TensorFlow, PyTorch) or experience with Generative AI (GenAI) and Large Language Models (LLMs).
• Proficiency with business intelligence and data visualization tools such as Tableau, Power BI, or Plotly.
• Experience working within Agile project delivery methodologies.

Competencies:

·        Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.

·        Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.

·        Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.

·        Customer Focus - Building strong customer relationships and delivering customer-centric solutions.

·        Optimizes Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.

Why Join Us?

• Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
• Work on impactful projects that make a difference across industries.
• Opportunities for professional growth and continuous learning.
• Competitive salary and benefits package.

Job Description-

Responsibilities:

* Work on real-world computer vision problems

* Write robust industry-grade algorithms

* Leverage OpenCV, Python and deep learning frameworks to train models.

* Use Deep Learning technologies such as Keras, Tensorflow, PyTorch etc.

* Develop integrations with various in-house or external microservices.

* Must have experience in deployment practices (Kubernetes, Docker, containerization, etc.) and model compression practices

* Research latest technologies and develop proof of concepts (POCs).

* Build and train state-of-the-art deep learning models to solve Computer Vision related problems, including, but not limited to:

* Segmentation

* Object Detection

* Classification

* Objects Tracking

* Visual Style Transfer

* Generative Adversarial Networks

* Work alongside other researchers and engineers to develop and deploy solutions for challenging real-world problems in the area of Computer Vision

* Develop and plan Computer Vision research projects, in the terms of scope of work including formal definition of research objectives and outcomes

* Provide specialized technical / scientific research to support the organization on different projects for existing and new technologies

Skills:

* Object Detection

* Computer Science

* Image Processing

* Computer Vision

* Deep Learning

* Artificial Intelligence (AI)

* Pattern Recognition

* Machine Learning

* Data Science

* Generative Adversarial Networks (GANs)

* Flask

* SQL

• experience in algorithm development with a focus on signal processing, pattern recognition, machine learning, classification, data mining, and other areas of machine intelligence.
• Ability to analyse data streams from multiple sensors and develop algorithms to extract accurate and meaningful sport metrics.
• Should have a deeper understanding of IMU sensors and Biosensors like HRM, ECG
• A good understanding on Power and memory management on embedded platform

•  Expertise in the design of multitasking, event-driven, real-time firmware using C and understanding of RTOS concepts
• Knowledge of Machine learning, Analytical and methodical approaches to data analysis and verification and Python
• Prior experience on fitness algorithm development using IMU sensor
•  Interest in fitness activities and knowledge of human body anatomy

• 3+ years experience in practical implementation and deployment of ML based systems preferred.
• BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
• Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow