11+ Kofax Jobs in Pune | Kofax Job openings in Pune

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

Data driven decision-making is core to advertising technology at AdElement. We are looking for sharp, disciplined, and highly quantitative machine learning/ artificial intellignce engineers with big data experience and a passion for digital marketing to help drive informed decision-making. You will work with top-talent and cutting edge technology and have a unique opportunity to turn your insights into products influencing billions. The potential candidate will have an extensive background in distributed training frameworks, will have experience to deploy related machine learning models end to end, and will have some experience in data-driven decision making of machine learning infrastructure enhancement. This is your chance to leave your legacy and be part of a highly successful and growing company.

Required Skills

- 3+ years of industry experience with Java/ Python in a programming intensive role

- 3+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, graph mining, deep learning

- 3+ years of industry experience with distributed computing frameworks such as Hadoop/Spark, Kubernetes ecosystem, etc

- 3+ years of industry experience with popular deep learning frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, etc

- 3+ years of industry experience with major cloud computing services

- An effective communicator with the ability to explain technical concepts to a non-technical audience

- (Preferred) Prior experience with ads product development (e.g., DSP/ad-exchange/SSP)

- Able to lead a small team of AI/ML Engineers to achieve business objectives

Responsibilities

- Collaborate across multiple teams - Data Science, Operations & Engineering on unique machine learning system challenges at scale

- Leverage distributed training systems to build scalable machine learning pipelines including ETL, model training and deployments in Real-Time Bidding space. 

- Design and implement solutions to optimize distributed training execution in terms of model hyperparameter optimization, model training/inference latency and system-level bottlenecks  

- Research state-of-the-art machine learning infrastructures to improve data healthiness, model quality and state management during the lifecycle of ML models refresh.

- Optimize integration between popular machine learning libraries and cloud ML and data processing frameworks. 

- Build Deep Learning models and algorithms with optimal parallelism and performance on CPUs/ GPUs.

- Work with top management on defining teams goals and objectives.

Education

- MTech or Ph.D. in Computer Science, Software Engineering, Mathematics or related fields

• Develop, train, and optimize machine learning models using Python, ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and other relevant technologies.
• Implement MLOps best practices, including model deployment, monitoring, and versioning.
• Utilize Vertex AI, MLFlow, KubeFlow, TFX, and other relevant MLOps tools and frameworks to streamline the machine learning lifecycle.
• Collaborate with cross-functional teams to design and implement CI/CD pipelines for continuous integration and deployment using tools such as GitHub Actions, TeamCity, and similar platforms.
• Conduct research and stay up-to-date with the latest advancements in machine learning, deep learning, and MLOps technologies.
• Provide guidance and support to data scientists and software engineers on best practices for machine learning development and deployment.
• Assist in developing tooling strategies by evaluating various options, vendors, and product roadmaps to enhance the efficiency and effectiveness of our AI and data science initiatives.

We are looking for Data Scientists with product exposure.

Work on Technical Machine Learning, AI and Software Projects

Capture use case and stakeholder requirements, document and in review with architecture team ensure requirements align to relevant features of a release.  

Capture a quantification of benefit each feature would bring to stakeholder and how adopting the product would materialize this.

Leveraging the articulation of benefit and impact of features develop a prioritization for next iteration of the product.

Develop the requirements and usage into effective user journeys which aligns to the AI / ML lifecycle.

Carry out industrial research on topic related to product and product families to ensure requirements and propose release align to industry best practices.

Support the documentation generation process to ensure end users will have sufficient information a the correct level of detail to leverage the product.

Support the UAT and testing stages in line with requirements captured by end users.

Interlock with end users to evaluate the effectiveness of the solution and if the pain points / requirements have been addressed

Responsibilities:

• Identify relevant data sources - a combination of data sources to make it useful.
• Build the automation of the collection processes.
• Pre-processing of structured and unstructured data.
• Handle large amounts of information to create the input to analytical Models.
• Build predictive models and machine-learning algorithms Innovate Machine-Learning , Deep-Learning algorithms.
• Build Network graphs , NLP , Forecasting Models Building data pipelines for end-to-end solutions.
• Propose solutions and strategies to business challenges. Collaborate with product development teams and communicate with the Senior Leadership teams.
• Participate in Problem solving sessions

Requirements:

• Bachelor's degree in a highly quantitative field (e.g. Computer Science , Engineering , Physics , Math , Operations Research , etc) or equivalent experience.
• Extensive machine learning and algorithmic background with a deep level understanding of at least one of the following areas: supervised and unsupervised learning methods , reinforcement learning , deep learning , Bayesian inference , Network graphs , Natural Language Processing Analytical mind and business acumen
• Strong math skills (e.g. statistics , algebra)
• Problem-solving aptitude Excellent communication skills with ability to communicate technical information.
• Fluency with at least one data science/analytics programming language (e.g. Python , R , Julia).
• Start-up experience is a plus Ideally 5-8 years of advanced analytics experience in startups/marquee com

Required Skills:

Machine Learning, Deep Learning, Algorithms, Computer Science, Engineering, Operations Research, Math Skills, Communication Skills, SAAS Product, IT Services, Artificial Intelligence, ERP, Product Management, Automation, Analytical Models, Predictive Models, NLP, Forecasting Models, Product Development, Leadership, Problem Solving, Unsupervised Learning, Reinforcement Learning, Natural Language Processing, Algebra, Data Science, Programming Language, Python, Julia

Job Summary

As a Data Science Lead, you will manage multiple consulting projects of varying complexity and ensure on-time and on-budget delivery for clients. You will lead a team of data scientists and collaborate across cross-functional groups, while contributing to new business development, supporting strategic business decisions and maintaining & strengthening client base

1. Work with team to define business requirements, come up with analytical solution and deliver the solution with specific focus on Big Picture to drive robustness of the solution
2. Work with teams of smart collaborators. Be responsible for their appraisals and career development.
3. Participate and lead executive presentations with client leadership stakeholders.
4. Be part of an inclusive and open environment. A culture where making mistakes and learning from them is part of life
5. See how your work contributes to building an organization and be able to drive Org level initiatives that will challenge and grow your capabilities.

​​​​​​Role & Responsibilities

1. Serve as expert in Data Science, build framework to develop Production level DS/AI models.
2. Apply AI research and ML models to accelerate business innovation and solve impactful business problems for our clients.
3. Lead multiple teams across clients ensuring quality and timely outcomes on all projects.
4. Lead and manage the onsite-offshore relation, at the same time adding value to the client.
5. Partner with business and technical stakeholders to translate challenging business problems into state-of-the-art data science solutions.
6. Build a winning team focused on client success. Help team members build lasting career in data science and create a constant learning/development environment.
7. Present results, insights, and recommendations to senior management with an emphasis on the business impact.
8. Build engaging rapport with client leadership through relevant conversations and genuine business recommendations that impact the growth and profitability of the organization.
9. Lead or contribute to org level initiatives to build the Tredence of tomorrow.

Qualification & Experience

1. Bachelor's /Master's /PhD degree in a quantitative field (CS, Machine learning, Mathematics, Statistics, Data Science) or equivalent experience.
2. 6-10+ years of experience in data science, building hands-on ML models
3. Expertise in ML – Regression, Classification, Clustering, Time Series Modeling, Graph Network, Recommender System, Bayesian modeling, Deep learning, Computer Vision, NLP/NLU, Reinforcement learning, Federated Learning, Meta Learning.
4. Proficient in some or all of the following techniques: Linear & Logistic Regression, Decision Trees, Random Forests, K-Nearest Neighbors, Support Vector Machines ANOVA , Principal Component Analysis, Gradient Boosted Trees, ANN, CNN, RNN, Transformers.
5. Knowledge of programming languages SQL, Python/ R, Spark.
6. Expertise in ML frameworks and libraries (TensorFlow, Keras, PyTorch).
7. Experience with cloud computing services (AWS, GCP or Azure)
8. Expert in Statistical Modelling & Algorithms E.g. Hypothesis testing, Sample size estimation, A/B testing
9. Knowledge in Mathematical programming – Linear Programming, Mixed Integer Programming etc , Stochastic Modelling – Markov chains, Monte Carlo, Stochastic Simulation, Queuing Models.
10. Experience with Optimization Solvers (Gurobi, Cplex) and Algebraic programming Languages(PulP)
11. Knowledge in GPU code optimization, Spark MLlib Optimization.
12. Familiarity to deploy and monitor ML models in production, delivering data products to end-users.
13. Experience with ML CI/CD pipelines.

Specialism- Advance Analytics, Data Science, regression, forecasting, analytics, SQL, R, python, decision tree, random forest, SAS, clustering classification

Senior Analytics Consultant- Responsibilities

• Understand business problem and requirements by building domain knowledge and translate to data science problem
• Conceptualize and design cutting edge data science solution to solve the data science problem, apply design thinking concepts
• Identify the right algorithms , tech stack , sample outputs required to efficiently adder the end need
• Prototype and experiment the solution to successfully demonstrate the value
  Independently or with support from team execute the conceptualized solution as per plan by following project management guidelines
• Present the results to internal and client stakeholder in an easy to understand manner with great story telling, story boarding, insights and visualization
• Help build overall data science capability for eClerx through support in pilots, pre sales pitches, product development , practice development initiatives