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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 

Purpose of Job:
Responsible to lead a team of analysts to build and deploy predictive models to infuse core
business functions with deep analytical insights. The Senior Data Scientist will also work
closely with the Kinara management team to investigate strategically important business questions.

Job Responsibilities:

Lead a team through the entire analytical and machine learning model life cycle:
 Define the problem statement
 Build and clean datasets
 Exploratory data analysis
 Feature engineering
 Apply ML algorithms and assess the performance
 Code for deployment
 Code testing and troubleshooting
 Communicate Analysis to Stakeholders
 Manage Data Analysts and Data Scientists

Qualifications:
 Education: MS/MTech/Btech graduates or equivalent with a focus on data science and
quantitative fields (CS, Engineering, Mathematics, Economics)

 Work Experience: 5+ years in a professional role with 3+ years in ML/AI
Other Requirements: ⮚ Domain knowledge in Financial Services is a big plus

Skills & Competencies
Technical Skills
⮚ Aptitude in Math and Stats
⮚ Proven experience in the use of Python, SQL, DevOps
⮚ Excellent in programming (Python), stats tools, and SQL
⮚ Working knowledge of tools and utilities - AWS, Git, Selenium, Postman,Prefect, Airflow, PySpark

Soft Skills
⮚ Deep Curiosity and Humility
⮚ Strong communications verbal and written

Prismforce (www.prismforce.com) is a US Head quartered vertical SAAS product company , with development teams in India. We are Series-A funded venture , backed by Tier 1 VC and targeted towards tech/IT services industry and tech talent organizations in enterprises, solving their most critical sector specific problems in Talent Supply Chain. The product suite is powered by artificial intelligence designed to accelerate business impact e.g. improved profitability and agility , by digitizing core vertical workflows underserved by custom applications and typical ERP offerings.

We are looking for Data Scientists to build data products to be the core of SAAS company disrupting the Skill market.In this role you should be highly analytical with a keen understanding of Data, Machine Learning, Deep Learning, Analysis, Algorithms, Products, Maths, and Statistics. The hands-on individual would be playing multiple roles of being a Data Scientist , Data Engineer , Data Analysts , Efficient Coder and above all Problem Solver.

Location: Mumbai / Bangalore / Pune / Kolkata

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

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.

About the Role:  

As a Speech Engineer you will be working on development of on-device multilingual speech recognition systems. 

• Apart from ASR you will be working on solving speech focused research problems like speech enhancement, voice analysis and synthesis etc. 
• You will be responsible for building complete pipeline for speech recognition from data preparation to deployment on edge devices. 
• Reading, implementing and improving baselines reported in leading research papers will be another key area of your daily life at Saarthi. 

Requirements:  

• 2-3 year of hands-on experience in speech recognitionbased projects 
• Proven experience as a Speech engineer or similar role 
• Should have experience of deployment on edge devices 
• Candidate should have hands-on experience with open-source tools such as Kaldi, Pytorch-Kaldi and any of the end-to-end ASR tools such as ESPNET or EESEN or DeepSpeech Pytorch
• Prior proven experience in training and deployment of deep learning models on scale 
• Strong programming experience in Python,C/C++, etc. 
• Working experience with Pytorch and Tensorflow
• Experience contributing to research communities including publications at conferences and/or journals 
• Strong communication skills 
• Strong analytical and problem-solving skills