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B1 – Data Scientist  -  Kofax Accredited Developers

Requirement – 3

Mandatory –

• Accreditation of Kofax KTA / KTM
• Experience in Kofax Total Agility Development – 2-3 years minimum
• Ability to develop and translate functional requirements to design
• Experience in requirement gathering, analysis, development, testing, documentation, version control, SDLC, Implementation and process orchestration
• Experience in Kofax Customization, writing Custom Workflow Agents, Custom Modules, Release Scripts
• Application development using Kofax and KTM modules
• Good/Advance understanding of Machine Learning /NLP/ Statistics
• Exposure to or understanding of RPA/OCR/Cognitive Capture tools like Appian/UI Path/Automation Anywhere etc
• Excellent communication skills and collaborative attitude
• Work with multiple teams and stakeholders within like Analytics, RPA, Technology and Project management teams
• Good understanding of compliance, data governance and risk control processes

Total Experience – 7-10 Years in BPO/KPO/ ITES/BFSI/Retail/Travel/Utilities/Service Industry

Good to have

• Previous experience of working on Agile & Hybrid delivery environment
• Knowledge of VB.Net, C#( C-Sharp ), SQL Server , Web services

Qualification -

• Masters in Statistics/Mathematics/Economics/Econometrics Or BE/B-Tech, MCA or MBA 

Job Description:

1.Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges

a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem

b. Improve Model accuracy to deliver greater business impact

c.Estimate business impact due to deployment of model

2.Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge

3.Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines

4.Design , develop & deploy Deep learning models using Tensorflow / Pytorch 

5.Experience in using Deep learning models with text, speech, image and video data

a.Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc

b.Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV

c.Knowledge of State of the art Deep learning algorithms

6.Optimize and tune Deep Learnings model for best possible accuracy

7.Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau

8.Work with application teams, in deploying models on cloud as a service or on-prem

a.Deployment of models in Test / Control framework for tracking

b.Build CI/CD pipelines for ML model deployment

9.Integrating AI&ML models with other applications using REST APIs and other connector technologies

10.Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.

· Technology/Subject Matter Expertise

• Sufficient expertise in machine learning, mathematical and statistical sciences
• Use of versioning & Collaborative tools like Git / Github
• Good understanding of landscape of AI solutions – cloud, GPU based compute, data security and privacy, API gateways, microservices based architecture, big data ingestion, storage and processing, CUDA Programming
• Develop prototype level ideas into a solution that can scale to industrial grade strength
• Ability to quantify & estimate the impact of ML models.

· Softskills Profile

• Curiosity to think in fresh and unique ways with the intent of breaking new ground.
• Must have the ability to share, explain and “sell” their thoughts, processes, ideas and opinions, even outside their own span of control
• Ability to think ahead, and anticipate the needs for solving the problem will be important

·        Ability to communicate key messages effectively, and articulate strong opinions in large forums

· Desirable Experience:

• Keen contributor to open source communities, and communities like Kaggle
• Ability to process Huge amount of Data using Pyspark/Hadoop
• Development & Application of Reinforcement Learning
• Knowledge of Optimization/Genetic Algorithms
• Operationalizing Deep learning model for a customer and understanding nuances of scaling such models in real scenarios
• Optimize and tune deep learning model for best possible accuracy
• Understanding of stream data processing, RPA, edge computing, AR/VR etc
• Appreciation of digital ethics, data privacy will be important
• Experience of working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud will all be a big plus
• Experience in platforms like Data robot, Cognitive scale, H2O.AI etc will all be a big plus

Position: Manager/Head- Data Scientist/Machine Learning Engineer

• Algorithm Development: Develop cutting-edge algorithms and predictive models to enhance customer experience, optimize inventory management, and drive sales growth
• AI/ML Model Building: Utilize expertise in data science and machine learning to create scalable AI models specifically tailored for both online platforms and brick-and-mortar stores, aiming to improve operational efficiency and customer engagement.
• Ecommerce Optimization: Collaborate with cross-functional teams to implement data-driven solutions for personalized recommendations, demand forecasting, and dynamic pricing strategies to drive online sales and enhance customer satisfaction.
• Deep Learning & Image Recognition: Leverage advanced techniques in deep learning and image recognition to develop innovative solutions for product categorization, visual search, and inventory tracking, optimizing product discovery and inventory management.
• Python Development: Proficiency in Python programming is essential for designing, implementing, and maintaining robust and scalable machine learning pipelines and models, ensuring efficient deployment and integration into existing systems.

Qualifications and Experience:

• Bachelor’s/Master’s degree in Computer Science, Data Science, Statistics, or related fields.
• 3 to 4 years of hands-on experience in data science, machine learning, and deep learning, preferably within the ecommerce or retail sector.
• Proven track record of successful implementation of AI/ML models with tangible business impact.
• Strong proficiency in Python, along with familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience working with image data, including feature extraction, object detection, and classification.
• Excellent problem-solving skills, ability to work independently, and communicate complex technical concepts effectively to diverse stakeholders.

THE IDEAL CANDIDATE WILL

• Engage with executive level stakeholders from client's team to translate business problems to high level solution approach
• Partner closely with practice, and technical teams to craft well-structured comprehensive proposals/ RFP responses clearly highlighting Tredence’s competitive strengths relevant to Client's selection criteria
• Actively explore the client’s business and formulate solution ideas that can improve process efficiency and cut cost, or achieve growth/revenue/profitability targets faster
• Work hands-on across various MLOps problems and provide thought leadership
• Grow and manage large teams with diverse skillsets
• Collaborate, coach, and learn with a growing team of experienced Machine Learning Engineers and Data Scientists

ELIGIBILITY CRITERIA

• BE/BTech/MTech (Specialization/courses in ML/DS)
• At-least 7+ years of Consulting services delivery experience
• Very strong problem-solving skills & work ethics
• Possesses strong analytical/logical thinking, storyboarding and executive communication skills
• 5+ years of experience in Python/R, SQL
• 5+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting
• Hands on work experience in DevOps
• Should have good knowledge in different deployment type like PaaS, SaaS, IaaS
• Exposure on cloud technologies like Azure, AWS or GCP
• Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
• Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc
• Experience with one or more Container-ecosystem (Docker, Kubernetes)
• Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
• Good understanding of OOP & Data Structures concepts

Nice to Have:

• Exposure to deployment strategies like: Blue/Green, Canary, AB Testing, Multi-arm Bandit
• Experience in Helm is a plus
• Strong understanding of data infrastructure, data warehouse, or data engineering

You can expect to –

• Work with world’ biggest retailers and help them solve some of their most critical problems. Tredence is a preferred analytics vendor for some of the largest Retailers across the globe
• Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
• Work in a diverse environment that keeps evolving
• Hone your entrepreneurial skills as you contribute to growth of the organization

We are looking for an outstanding Big Data Engineer with experience setting up and maintaining Data Warehouse and Data Lakes for an Organization. This role would closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Roles and Responsibilities:

• Develop and maintain scalable data pipelines and build out new integrations and processes required for optimal extraction, transformation, and loading of data from a wide variety of data sources using 'Big Data' technologies.
• Develop programs in Scala and Python as part of data cleaning and processing.
• Assemble large, complex data sets that meet functional / non-functional business requirements and fostering data-driven decision making across the organization.  
• Responsible to design and develop distributed, high volume, high velocity multi-threaded event processing systems.
• Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Provide high operational excellence guaranteeing high availability and platform stability.
• Closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Skills:

• Experience with Big Data pipeline, Big Data analytics, Data warehousing.
• Experience with SQL/No-SQL, schema design and dimensional data modeling.
• Strong understanding of Hadoop Architecture, HDFS ecosystem and eexperience with Big Data technology stack such as HBase, Hadoop, Hive, MapReduce.
• Experience in designing systems that process structured as well as unstructured data at large scale.
• Experience in AWS/Spark/Java/Scala/Python development.
• Should have Strong skills in PySpark (Python & SPARK). Ability to create, manage and manipulate Spark Dataframes. Expertise in Spark query tuning and performance optimization.
• Experience in developing efficient software code/frameworks for multiple use cases leveraging Python and big data technologies.
• Prior exposure to streaming data sources such as Kafka.
• Should have knowledge on Shell Scripting and Python scripting.
• High proficiency in database skills (e.g., Complex SQL), for data preparation, cleaning, and data wrangling/munging, with the ability to write advanced queries and create stored procedures.
• Experience with NoSQL databases such as Cassandra / MongoDB.
• Solid experience in all phases of Software Development Lifecycle - plan, design, develop, test, release, maintain and support, decommission.
• Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development).
• Experience building and deploying applications on on-premise and cloud-based infrastructure.
• Having a good understanding of machine learning landscape and concepts. 

Qualifications and Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Big Data Engineer or a similar role for 3-5 years.

Certifications:

Good to have at least one of the Certifications listed here:

    AZ 900 - Azure Fundamentals

    DP 200, DP 201, DP 203, AZ 204 - Data Engineering

    AZ 400 - Devops Certification