Data Scientist (Kofax Accredited Developers)

Job Title -Data Scientist

Job Duties

1. Data Scientist responsibilities includes planning projects and building analytics models.
2. You should have a strong problem-solving ability and a knack for statistical analysis.
3. If you're also able to align our data products with our business goals, we'd like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data.

Responsibilities

Own end-to-end business problems and metrics, build and implement ML solutions using cutting-edge technology.

Create scalable solutions to business problems using statistical techniques, machine learning, and NLP.

Design, experiment and evaluate highly innovative models for predictive learning

Work closely with software engineering teams to drive real-time model experiments, implementations, and new feature creations

Establish scalable, efficient, and automated processes for large-scale data analysis, model development, deployment, experimentation, and evaluation.

Research and implement novel machine learning and statistical approaches.

Requirements

2-5 years of experience in data science.

In-depth understanding of modern machine learning techniques and their mathematical underpinnings.

Demonstrated ability to build PoCs for complex, ambiguous problems and scale them up.

Strong programming skills (Python, Java)

High proficiency in at least one of the following broad areas: machine learning, statistical modelling/inference, information retrieval, data mining, NLP

Experience with SQL and NoSQL databases

Strong organizational and leadership skills

Excellent communication skills

• Bring in industry best practices around creating and maintaining robust data pipelines for complex data projects with/without AI component
  • programmatically ingesting data from several static and real-time sources (incl. web scraping)
  • rendering results through dynamic interfaces incl. web / mobile / dashboard with the ability to log usage and granular user feedbacks
  • performance tuning and optimal implementation of complex Python scripts (using SPARK), SQL (using stored procedures, HIVE), and NoSQL queries in a production environment

• Industrialize ML / DL solutions and deploy and manage production services; proactively handle data issues arising on live apps
• Perform ETL on large and complex datasets for AI applications - work closely with data scientists on performance optimization of large-scale ML/DL model training
• Build data tools to facilitate fast data cleaning and statistical analysis
• Ensure data architecture is secure and compliant
• Resolve issues escalated from Business and Functional areas on data quality, accuracy, and availability
• Work closely with APAC CDO and coordinate with a fully decentralized team across different locations in APAC and global HQ (Paris).

•  Expert in structured and unstructured data in traditional and Big data environments – Oracle / SQLserver, MongoDB, Hive / Pig, BigQuery, and Spark
• Have excellent knowledge of Python programming both in traditional and distributed models (PySpark)
• Expert in shell scripting and writing schedulers
• Hands-on experience with Cloud - deploying complex data solutions in hybrid cloud / on-premise environment both for data extraction/storage and computation
• Hands-on experience in deploying production apps using large volumes of data with state-of-the-art technologies like Dockers, Kubernetes, and Kafka
• Strong knowledge of data security best practices
• 5+ years experience in a data engineering role
• Science / Engineering graduate from a Tier-1 university in the country
• And most importantly, you must be a passionate coder who really cares about building apps that can help people do things better, smarter, and faster even when they sleep

Graas uses predictive AI to turbo-charge growth for eCommerce businesses. We are “Growth-as-a-Service”. Graas is a technology solution provider using predictive AI to turbo-charge growth for eCommerce businesses. Graas integrates traditional data silos and applies a machine-learning AI engine, acting as an in-house data scientist to predict trends and give real-time insights and actionable recommendations for brands. The platform can also turn insights into action by seamlessly executing these recommendations across marketplace store fronts, brand.coms, social and conversational commerce, performance marketing, inventory management, warehousing, and last mile logistics - all of which impacts a brand’s bottom line, driving profitable growth.

Location – Pune

Job Responsibilities

• Work closely with data scientists and data analysts to build models and continuous data monitoring workflows.
• Implement algorithms / models within companies recommendation engine framework.
• Own the MLOps life-cycle; build and own ML model life-cycle management process encompassing coding to building robust model monitoring workflows.
• Consult with product and business teams to build prototypes and then deploy holistic machine learning solutions.
• Recommend and implement architecture to deploy machine learning pipelines and CI/CD processes at scale

Skills Needed

• Minimum 3 years of experience as Machine Learning Engineer
• Knowledge of machine learning and statistics
• Strong experience working in the areas of time series analysis, reinforcement learning, NLP, optimization and heuristics based implementation to solve real-world problems
• Experienced in architecting solutions with Continuous Integration and Continuous Delivery in mind
• Strong knowledge of coding in Python and libraries such as Pandas, Numpy, Scikit-Learn, PyTorch, etc.
• Experience handling Big Data leveraging technologies like Snowflake, Spark. Ability to work in a big data ecosystem - expert in SQL and ability to work in distributed databases.
• Able to refactor data science code and has collaborated with data scientists in developing ML solutions.
• Experience playing the role of full-stack data scientist and taking solutions to production.
• Educational qualifications should be preferably in Computer Science, Statistics, Engineering or a related area.

Responsibilities

1. Create data funnels to feed into models via web, structured and unstructured data
2. Maintain coding standards using  SDLC, Git, AWS deployments etc
3. Keep abreast of developments in the field
4. Deploy models in production and monitor them
5. Documentations of processes and logic
6. Take ownership of the solution from code to deployment and performance

- Modeling complex problems, discovering insights, and identifying opportunities through the use of statistical, algorithmic, mining, and visualization techniques

- Experience working with business understanding the requirement, creating the problem statement, and building scalable and dependable Analytical solutions

- Must have hands-on and strong experience in Python

- Broad knowledge of fundamentals and state-of-the-art in NLP and machine learning

- Strong analytical & algorithm development skills

- Deep knowledge of techniques such as Linear Regression, gradient descent, Logistic Regression, Forecasting, Cluster analysis, Decision trees, Linear Optimization, Text Mining, etc

- Ability to collaborate across teams and strong interpersonal skills

Skills

- Sound theoretical knowledge in ML algorithm and their application

- Hands-on experience in statistical modeling tools such as R, Python, and SQL

- Hands-on experience in Machine learning/data science

- Strong knowledge of statistics

- Experience in advanced analytics / Statistical techniques – Regression, Decision trees, Ensemble machine learning algorithms, etc

- Experience in Natural Language Processing & Deep Learning techniques 

- Pandas, NLTK, Scikit-learn, SpaCy, Tensorflow

• 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